Parsity

Parsity is a full-stack AI program.

Learn the fundamentals of software development with a modern web stack and applied AI skills such as RAG, vector databases, AI observability and cloud deployment.

Small cohorts, big success stories and expert mentors. 

Visit Parsity.io to apply.

Program Owner

Influur

As the first hire on the web engineering team, I partnered directly with the CEOS and CTO to build an AI-powered influencer matching platform helping the world’s biggest record labels connect with creators. 

I worked across the entire stack—from front-end prototypes in Next.js + TypeScript to back-end services, data pipelines, and proof-of-concepts—taking the product from zero to one.

I designed and shipped the first data pipelines ingesting hundreds of thousands of TikTok data points daily, powering campaign insights at scale. I also implemented our first retrieval-augmented generative (RAG) database using GCP (Vertex AI, BigQuery, Firebase) and OpenAI models, enabling AI-driven recommendations and analysis. 

My work combined fast iteration with strong engineering fundamentals, blending modern AI development with traditional software practices to accelerate innovation.

Senior Full Stack AI Engineer

Scoutbee

Founding team member at an early-stage AI-driven procurement startup, working closely with the Head of Engineering, product, and go-to-market teams to shape product direction.

Contributed to the development and implementation of an AI-powered chat feature using Retrieval-Augmented Generation (RAG) with Pinecone and OpenAI’s API, enabling users to quickly retrieve supplier insights.

Developed and implemented multiple key features, including in-app messaging, Stripe integration, and custom landing pages to improve user experience and streamline business operations.

Utilizing TypeScript, Prisma, PostgreSQL, Next.js, React, and Vercel to develop scalable, AI-driven procurement solutions.

Collaborating in a small, agile team to refine the core product architecture, improve internal tooling, and accelerate product development.

Senior Full Stack Engineer

Archwell

This was a short yet impactful 1 month stint:

Led the planning of a migration from legacy systems to modern frameworks, including Next.js and CloudFront, focusing on scalability and code reusability.

Implemented a CI/CD pipeline that accelerated the migration process and improved overall development efficiency.

Provided technical leadership for modernizing the platform, helping the company establish a future-proof infrastructure.

Associate Director of Engineering

The Clorox Company

Democratized the release process, enabling engineers to deploy code seamlessly by adopting best practices in DevOps and continuous integration, facilitated by extensive use of Jest for comprehensive test coverage. Led the modernization of our front-end architecture, implementing ReactJS and Redux for state management, coupled with GraphQL for efficient data fetching, to create a robust, scalable, and highly maintainable web application framework.

Instrumental in elevating our engineering standards, I spearheaded the drive to enhance code quality, achieving an increase in test coverage from 0% to approximately 40% with Jest, thereby promoting a culture of code stewardship. This initiative paved the way for a more inclusive, collaborative, and ownership-driven development environment.

Oversaw the strategic migration of our front-end tech stack to leverage Adobe Commerce Cloud in a headless architecture, optimizing our e-commerce capabilities and user experience by integrating ReactJS, Redux, and GraphQL. This move not only improved performance and scalability but also enhanced developer agility in feature development.

Revamped our interview and onboarding processes to accelerate the vetting and hiring of talented developers. By fostering a rapid acclimatization within our ReactJS and GraphQL-based codebase, new team members could contribute significantly and efficiently early on in their tenure.

Developed and implemented a career-level guide to define clear advancement criteria and expectations at each level, ensuring transparent, merit-based growth paths within our technology organization, and supporting professional development

Engineering Manager

In my role within the Clorox DTC (Direct-to-Consumer) team, I spearhead the development of compelling online user experiences for Clorox's DTC brand partnerships, employing cutting-edge technologies such as ReactJS and ReduxJS, and harnessing the power of microservice architecture to ensure scalability and flexibility.

I introduced and championed the integration of unit testing across all front-end applications, utilizing Jest and @testing-library, to elevate code reliability and foster a culture of quality assurance from the onset of development.

Recognizing the need for efficiency and maintainability in our development process, I led the creation of a shared state management library specifically designed for micro frontends. This initiative significantly boosted developer productivity, curtailed code duplication, and streamlined our application's overall architecture.

Contributed to the design and implementation of a shared component library using ReactJS, facilitating a consistent and reusable codebase that accelerates development cycles and ensures UI/UX consistency across DTC platforms.

Collaborated with the team to devise a new Git flow strategy, optimizing our code release and hotfix processes to enhance operational efficiency and reduce time-to-market for new features and fixes.

As a mentor, I am committed to elevating the technical proficiency of our team members, guiding them in JavaScript best practices and testing methodologies to cultivate a high-caliber development team adept in modern web technologies.

Senior Software Engineer

Zignal Labs

Mentored and onboarded team mates in JavaScript best practices and coding standards.

Through investigation and optimization, I successfully enhanced the performance of a notably slow query in our NodeJS API, achieving a 50% improvement in speed. This optimization not only boosted our system's efficiency but also significantly enhanced user experience by providing faster access to critical data.

On the development front, I actively contributed to our ReactJS component library, focusing on expanding our data visualization capabilities. Notably, I spearheaded the integration of D3.js to develop our inaugural RidgeLine chart component, which represents trending Twitter topics.

At Zignal Labs, a forefront company in brand protection, we harness the power of extensive data aggregation from diverse mediums to deliver actionable insights that safeguard company reputations. As an integral part of the full-stack development team, my role is centered around designing and implementing dynamic widgets and robust APIs that enhance data visualization and user interaction.

Utilizing a sophisticated tech stack that includes NodeJS for server-side operations, MongoDB for scalable database solutions, ReactJS and Redux for seamless front-end user experiences, and ElasticSearch for efficient data querying and indexing, I contribute to developing innovative solutions that transform complex datasets into clear, intuitive visualizations.

My work supports clients in making informed decisions by providing them with real-time, visually compelling insights into their brand's performance across various channels. Through the creation of these widgets and APIs, I play a pivotal role in enabling Zignal Labs to offer a comprehensive suite of tools that empower companies to proactively manage and protect their brand integrity.

Software Engineer

Micasa

Micasa automates the manual process of complicated document transactions for purchasing homes
As the lead developer I built and deployed the backend services and UI as well influenced the general UX of the site

Created complex integrations with HelloSign API, deployed our NodeJS API on AWS using Lambdas and worked closely with founders to develop marketing strategy and technical direction.

Over the Summer of 2019 I led a small team of college interns to contribute to the project and identified relevant features for them to work on

Technologies included AWS, NodeJS, ReactJS, Redux. MongoDB

Co-Founder and Lead Fullstack Developer

Terminal 49

As a full stack software developer on the founding team I've had the opportunity to help create and implement new features for our logistics tech startup to help facilitate and automate international trade. Using Rails, Postgres and EmberJS I worked on projects including a system to request and send quotes, aggregate data to surface information about containers as they travel as well as a program to update container arrival times

Codify Academy

On weekends I was a lead mentor at Codify, a bootcamp that teaches students the basics of front-end development like JavaScript, React JS, HTML, CSS, Bootstrap and responsive design among other things. I also led development on a fullstack web app for the learning management system for Codify to use to track student progress and communicate with mentors and students.

Lead Front End Development Mentor

Grocery Outlet

As a full stack developer on the agile team that creates the web applications that power this 2 billion dollar business I had the chance lead development on one of our apps used to facilitate store returns which saved 10s of thousands dollars a year by preventing human error. 

Helped automate the process of unloading pallets from trucks through a program to bulk import product data.

Our small team also built a real time system for stores to order goods and many other web apps using C#, SQL, AngularJS and .NET

Web Application Developer

Besides being a talking head on LinkedIn, I lead software development teams, mentor developers and help career changers learn to write complex software.

At the core of all these efforts is a simple goal: empowering developers and magnifying their capabilities.

Sometimes that means changing processes to allow teams to move faster, deploy code with less friction and confidence. In my courses and programs, empowerment is making the abstract practical with lessons and challenges which mimic the experience of being a software developer.

If you actually read this, thanks. Always happy to connect and check out the links in about section 😉

Brian Jenney

This might lose me some business, but it needs to be said:
 
You can't stack AI skills on top of shaky software skills.
 
Before you dive into agents, RAG, or fine-tuning, you need real coding basics.
 
Do this first:

• 𝗚𝗲𝘁 𝗰𝗼𝗺𝗳𝗼𝗿𝘁𝗮𝗯𝗹𝗲 𝘄𝗶𝘁𝗵 𝗳𝘂𝗻𝗱𝗮𝗺𝗲𝗻𝘁𝗮𝗹𝘀: APIs, error handling, common design patterns and building and deploying full stack apps
• 𝗨𝗻𝗱𝗲𝗿𝘀𝘁𝗮𝗻𝗱 𝘁𝗵𝗲 𝗲𝘀𝘀𝗲𝗻𝘁𝗶𝗮𝗹 𝗔𝗜 𝗽𝗿𝗶𝗺𝗶𝘁𝗶𝘃𝗲𝘀: Tokens, embeddings, context windows. If those concepts feel fuzzy, everything advanced will feel like magic.

Here’s the truth:
 
AI engineering isn’t a shortcut. It’s software development with more moving parts and a rule book that is still being written.
 
If you don’t have a solid foundation you'll be building on a house of cards.

I Help Career Changers Become Software Developers Without Quitting Their Jobs

I’ve been posting on LinkedIn for 5 years but I don’t know if I’ve ever formally introduced myself.

I’m Brian, a 41-year-old software developer from Oakland, California.

Here’s my story so far:

𝟮𝟬𝟭𝟯
Got sober after an intervention. It was bad.
Suddenly had time. A lot of it.
No idea what life looked like next.

𝟮𝟬𝟭𝟰
Learned to code to fill the hours.
Got my first dev job at Grocery Outlet.
Made peanuts. Didn’t matter. I was getting paid to do what I loved.

𝟮𝟬𝟭𝟳
I got greedy.
Left for a startup.
Doubled my salary.
Anxiety, crippling doubt.
Realized how little I knew.

𝟮𝟬𝟭𝟳 - 𝟮𝟬𝟭𝟵
Another startup.
Study my ass off to fill in my technical gaps.
Promoted to senior developer.
Tried building my own startup and failed miserably.
Switched stacks from the failed startup project.

𝟮𝟬𝟭𝟵–𝟮𝟬𝟮𝟯
Moved again - this time to Clorox (the bleach company!).
Eventually managed a team.
Made the presentations. Hired. Fired. Managing!
Started quietly building an online business.
Laid off 😅

𝟮𝟬𝟮𝟱
Pivot to AI startups
Go from manager to senior software engineer. No ragrats.

And I own Parsity. A coding bootcamp… in 2025.

Today, we help around 30 people a year break into software, learn full-stack development, and build actual AI engineering skills — not “prompt engineering,” but the stuff companies actually hire for.

𝗜𝗳 𝘆𝗼𝘂 𝘄𝗮𝗻𝘁 𝘁𝗼 𝗯𝗿𝗲𝗮𝗸 𝗶𝗻𝘁𝗼 𝘁𝗲𝗰𝗵:

I make a ton of free resources for early learners.
Everything is in my bio.
If you want to apply to Parsity, you’ll find that there too.

𝗡𝗲𝘅𝘁 𝘆𝗲𝗮𝗿 𝗺𝘆 𝗴𝗼𝗮𝗹 𝗶𝘀 𝘀𝗶𝗺𝗽𝗹𝗲:
Help a handful of people make a real transition into software and learn the AI skills that will define the next few years.

How old is too old to learn to code?

According to the internet... it's 30.

Thank god Nils didn't take this advice.
 
When Nils came to Parsity, he was 44, switching careers, and had no idea how to break into tech.
 
Six months later?
 
𝗛𝗲’𝘀 𝗮 𝗳𝘂𝗹𝗹-𝘁𝗶𝗺𝗲 𝘀𝗼𝗳𝘁𝘄𝗮𝗿𝗲 𝗲𝗻𝗴𝗶𝗻𝗲𝗲𝗿 𝘄𝗶𝘁𝗵 𝗮 𝗵𝘆𝗯𝗿𝗶𝗱 𝘀𝗰𝗵𝗲𝗱𝘂𝗹𝗲, 𝘁𝗶𝗺𝗲 𝗳𝗼𝗿 𝗵𝗶𝘀 𝗳𝗮𝗺𝗶𝗹𝘆, 𝗮𝗻𝗱 𝗮 𝗰𝗹𝗲𝗮𝗿 𝗰𝗮𝗿𝗲𝗲𝗿 𝗽𝗮𝘁𝗵.
 
Here’s what changed:
 
𝟭. 𝗛𝗲 𝗳𝗼𝗹𝗹𝗼𝘄𝗲𝗱 𝗮 𝗿𝗲𝗮𝗹 𝘀𝘁𝗿𝘂𝗰𝘁𝘂𝗿𝗲 (𝗻𝗼𝘁 𝗬𝗼𝘂𝗧𝘂𝗯𝗲 𝗰𝗵𝗮𝗼𝘀)
• Started with Codecademy
• Joined Parsity for a guided curriculum and mentorship
• Treated coding like music: patterns, repetition, feedback
 
𝟮. 𝗛𝗲 𝘂𝘀𝗲𝗱 𝗵𝗶𝘀 𝗿𝗲𝗮𝗹 𝗻𝗲𝘁𝘄𝗼𝗿𝗸 (𝗻𝗼𝘁 𝘁𝗵𝗲 𝗷𝗼𝗯 𝗯𝗼𝗮𝗿𝗱𝘀)
• Reached out to former colleagues
• Got contract work through a local connection
• Landed his full-time role through a personal referral
 
𝗧𝗵𝗲 𝗿𝗲𝘀𝘂𝗹𝘁𝘀
• Full-time software engineer
• Moved his family to Kansas City
• Flexible hybrid schedule
• Supportive senior devs + mentorship
• Clear path to leadership
 
Nils didn’t get lucky.
 
He followed the right process and stayed consistent.
  
If you’re a busy adult and want to break into tech without wasting years...

DM me “𝗦𝗧𝗔𝗥𝗧.” I’ll send you the exact steps Nils followed.

If you’re a full stack dev and thinking you need to switch into ML - watch this first.

If you're preparing for a front end interview - read this:

Spoke to an acquaintance who works in big tech and just landed a role.

He’s done a dozen interviews across startups and a few companies you’ve heard of.

What he reported might surprise you:

Out of all those technical rounds, he only got 1 DSA problem.

Everything else was practical frontend work:

• autosuggest with debounce
• dashboards with error handling
• forms with range queries
• requestAnimationFrame timers
• pagination
• API contract design
• React fundamentals
  
He also moved to multiple final rounds after not fully completing the technical challenge.

If you’re still grinding LeetCode because you think that’s what frontend interviews look like in 2025 going into 2026, you’re studying for a test many companies aren’t giving.

Can I admit something?

I didn't really get MCP...

So today I sat down and created a small MCP server and integrated it with Claude.

This server exposes a couple tools that Claude can use to search EVERY piece of content I've written by querying a vector database and then apply that context to write a Linkedin post or article using my personal experiences and tone.

𝗦𝘁𝗲𝗽 𝟭: Chunk and store all my posts and articles into a vector DB (I used Qdrant)
𝗦𝘁𝗲𝗽 𝟮: Use @𝚖𝚘𝚍𝚎𝚕𝚌𝚘𝚗𝚝𝚎𝚡𝚝𝚙𝚛𝚘𝚝𝚘𝚌𝚘𝚕/𝚜𝚍𝚔 library to create and expose the tools in a Node/Express app
𝗦𝘁𝗲𝗽 𝟯: Run the server locally and use 𝚗𝚐𝚛𝚘𝚔 to expose it to publicly (𝘴𝘦𝘤𝘶𝘳𝘪𝘵𝘺 𝘱𝘦𝘦𝘱𝘴 𝘱𝘭𝘦𝘢𝘴𝘦 𝘥𝘰𝘯'𝘵 @ 𝘮𝘦)
𝗦𝘁𝗲𝗽 𝟰: Add the ngrok endpoint as a custom connector in Claude (𝘢𝘨𝘢𝘪𝘯, 𝘴𝘦𝘤𝘶𝘳𝘪𝘵𝘺 𝘧𝘰𝘭𝘬𝘴, 𝘥𝘰𝘯'𝘵 𝘩𝘢𝘵𝘦 𝘮𝘦 𝘱𝘭𝘻)
𝗦𝘁𝗲𝗽 𝟱: 😎

While the AI bros and normies continue to freak out about AGI and AI taking over our jobs - I'd encourage you to actually play with some of the tech out there. 

This has got to be one of the most fun times to be writing code.

The developer community needs less:

- 1,000-hour “free” YouTube epics you’ll never finish
- Interview grind content aimed at the top 1% of big tech
- “𝘋𝘢𝘺 𝘪𝘯 𝘵𝘩𝘦 𝘓𝘪𝘧𝘦” vlogs (aka layoff teasers) that glamorize the job but don’t teach it

And more:

- Hands-on GitHub repos you actually clone, break, and fix
- Text-based guides you can skim, search, and return to when you’re stuck
- Honest write-ups of outages, failures and on-call shifts. Not just highlight reels

Most junior devs don’t need more entertainment.

They need practical reps with real code, real constraints, and real problems.

3 students from Parsity just got hired.

They’re talented, amazing people and well deserving. And they’re not much different than you. 

They felt uncertain. 
Like it would never happen. 
That maybe they just weren’t good enough.

When I think of all the mentees I’ve seen get hired over the years, there are few hard and fast rules.

- Most did NOT learn in public.
- Some mass-applied.
- A few networked their way to the first role.
- Many of their interviews were barely technical. 
- Some ONLY got LeetCode problems.

Your timeline will be unpredictable.

Be persistent, practically optimistic that opportunity will present itself, re-calibrate when you see things not working, maintain your skills and your own success will be inevitable.

I’ve worked with hundreds of career changers and early career developers.

Here’s how the successful ones operate:
 
They do the uncomfortable stuff.
 
• Reach out to real people in their 𝗿𝗲𝗮𝗹 𝗻𝗲𝘁𝘄𝗼𝗿𝗸. Not JUST online.
• 𝗕𝗼𝗺𝗯 𝗶𝗻𝘁𝗲𝗿𝘃𝗶𝗲𝘄𝘀, learn from them, and move on. Not crawl in a code hole of despair.
• 𝗕𝘂𝗶𝗹𝗱 𝟭 𝗼𝗿 𝟮 𝗶𝗻𝘁𝗲𝗿𝗲𝘀𝘁𝗶𝗻𝗴 𝗽𝗿𝗼𝗷𝗲𝗰𝘁𝘀 instead of a dozen portfolio projects.
• They're 𝗽𝗿𝗮𝗰𝘁𝗶𝗰𝗮𝗹𝗹𝘆 𝗼𝗽𝘁𝗶𝗺𝗶𝘀𝘁𝗶𝗰. They accept things will suck but not forever.
 
This is how you can become a hire-able developer without being the smartest person in the room.

• If you want confidence, then collect proof of what you learn. Record yourself. Journal. Push code.
• If you want a network, then talk to people online and in person.
• If you want opportunities, then do the things you avoid.

Simple, effective, repeatable.

Easy? Not really.
 
I’ve seen this pattern for years: the people who win aren’t always the most talented. They’re the ones who stay curious, build cool shit, stay flexible, and refuse to give up.

5 biggest mistakes of my coding career (so far):

1. Being afraid to admit when I didn’t know something 
2. Not learning the fundamentals before diving into frameworks 
3. Only taking on tasks I knew I could finish 
4. Not understanding how code fits into the company eco-system and business goals 
𝟱. 𝗡𝗼𝘁 𝘀𝗽𝗲𝗮𝗸𝗶𝗻𝗴 𝘂𝗽 

That last one hurt me the most. 

I thought I was playing it safe by taking on easy tickets. I nodded my head during estimation sessions and gave bland status updates. I never shared my ideas during meetings.

I wanted to blend in.

It was the most dangerous thing I could’ve done. 

There's a saying - "𝘵𝘩𝘦 𝘵𝘢𝘭𝘭𝘦𝘴𝘵 𝘣𝘭𝘢𝘥𝘦 𝘰𝘧 𝘨𝘳𝘢𝘴𝘴 𝘪𝘴 𝘵𝘩𝘦 𝘧𝘪𝘳𝘴𝘵 𝘵𝘰 𝘨𝘦𝘵 𝘤𝘶𝘵." 

It’s also the one growing the fastest. 

Companies need average developers more than they’d like to admit. But, if career trajectory and increased hire-ability is your goal, then playing it safe is your greatest threat.

Let's go old school.

No vibe coding.
No AI.

We're going to plan out your next side project using a process I use today when I have no clue what to make.

Over the years my side projects have helped me switch tech stacks, made me some money and kept my skills relevant.

If you have no clue what to build - by the end of the workshop you'll have a plan of action that will NOT suck.

Ghadeer Albattarni, Mike Hasson and 75 other attendees

Better than LeetCode.

And free-er too.

Every year a large community of developers join Advent of Code for Christmas-themed coding challenges.

I usually get through the first week or 2 before I tap out.

The first couple days are typically doable for beginners and a good litmus test of your problem solving skills.

Career advice that sounded good on paper but didn't work for me:

1. Don't get involved in office politics
2. You don't need DSA (𝑤ℎ𝑖𝑡𝑒𝑏𝑜𝑎𝑟𝑑 𝑖𝑛𝑡𝑒𝑟𝑣𝑖𝑒𝑤𝑠 𝑎𝑟𝑒 𝑏𝑖𝑎𝑠𝑒𝑑)
3. Stay at each company for 2 years minimum
4. Impostor syndrome is all in your head
5. Hard work will get you promoted

As an outsider to tech from an about as non-traditional background as you can imagine - I learned what works for others wouldn't really work for me. 

Here's some career advice I've gathered over the last 11 years that the LinkedIn mob won't tell you.

I want to offer you some politically incorrect career advice. The stuff that took me years to figure out that the gurus on LinkedIn won’t ever tell yo

Open article: Forbidden Career Advice for Software Developers (The Stuff No One Tells You) by Brian Jenney • 7 min read

Forbidden Career Advice for Software Developers (The Stuff No One Tells You)

When I decided to learn AI, I started completely in the wrong place. 

I went straight into ML engineering books, LLM architecture deep dives, and even tried learning how to build a large language model from scratch.
 
As a full-stack developer, that wasn’t the path that helped me understand how to actually use this stuff.
 
Here are 𝟯 𝘀𝘁𝗲𝗽𝘀 that helped me build real intuition ↓

 
𝟭. 𝗦𝘁𝗮𝗿𝘁 𝘄𝗶𝘁𝗵 𝗹𝗶𝗻𝗲𝗮𝗿 𝗮𝗹𝗴𝗲𝗯𝗿𝗮 𝗳𝗼𝗿 𝗱𝘂𝗺𝗺𝗶𝗲𝘀

• Get the basics: dot product, cosine similarity, and how vectors actually 𝘣𝘦𝘩𝘢𝘷𝘦.
• Search “3Blue1Brown linear algebra” on YouTube.  The visuals make everything click.
• Understanding vectors will give you some intuition for how step #2 works .


𝟮. 𝗦𝗵𝗶𝗽 𝗮 𝗺𝗶𝗻𝗶 𝗥𝗔𝗚 𝘀𝘆𝘀𝘁𝗲𝗺

• Find some documents you have available, embed them, store vectors in Qdrant or Pinecone, and build an “ask your documents” search.
• This alone will give you more intuition than 40 pages of math.


𝟯. 𝗕𝘂𝗶𝗹𝗱 𝗮 𝘀𝗶𝗺𝗽𝗹𝗲 𝗮𝗴𝗲𝗻𝘁 𝘄𝗼𝗿𝗸𝗳𝗹𝗼𝘄

• Build a workflow with at least 2 agents that handle separate tasks.
• Replicate that same flow using LangGraph (or similar) to understand the problems that agent frameworks solve.
• 𝗘𝘅𝗮𝗺𝗽𝗹𝗲: I built a system to search thousands of pieces of content I’ve written and retrieve them by tone, theme, or emotion and built this using different approaches.
 
Most developers read about AI long before they ever 𝘵𝘰𝘶𝘤𝘩 it. It should be the opposite.
  
𝙄𝙛 𝙮𝙤𝙪 𝙬𝙖𝙣𝙩 𝙨𝙤𝙢𝙚𝙩𝙝𝙞𝙣𝙜 𝙘𝙤𝙣𝙘𝙧𝙚𝙩𝙚 𝙩𝙤 𝙗𝙪𝙞𝙡𝙙, 𝙘𝙤𝙢𝙢𝙚𝙣𝙩 𝙤𝙧 𝘿𝙈 🤖 (𝙨𝙤 𝙄 𝙠𝙣𝙤𝙬 𝙮𝙤𝙪'𝙧𝙚 𝙣𝙤𝙩 𝙖 𝙧𝙤𝙗𝙤𝙩) 𝙖𝙣𝙙 𝙄’𝙡𝙡 𝙨𝙚𝙣𝙙 𝙮𝙤𝙪 𝟮 𝙥𝙧𝙖𝙘𝙩𝙞𝙘𝙖𝙡, 𝙘𝙤𝙙𝙚-𝙝𝙚𝙖𝙫𝙮 𝙚𝙭𝙚𝙧𝙘𝙞𝙨𝙚𝙨 𝙩𝙤 𝙜𝙚𝙩 𝙮𝙤𝙪 𝙢𝙤𝙫𝙞𝙣𝙜.

The human brain builds new neural pathways in as little as a few focused minutes a day.
 
But without structure, feedback, and accountability, those same pathways weaken just as fast as they’re created.
 
This explains why 𝘀𝗼𝗺𝗲 𝗱𝗲𝘃𝗲𝗹𝗼𝗽𝗲𝗿𝘀 𝗴𝗲𝘁 𝘀𝘁𝘂𝗰𝗸 𝗼𝗻 𝗮 𝗹𝗲𝗮𝗿𝗻𝗶𝗻𝗴 𝗵𝗮𝗺𝘀𝘁𝗲𝗿 𝘄𝗵𝗲𝗲𝗹.
 
Inconsistency becomes the biggest killer of progress.

You feel “behind,” get discouraged, and fall out of the habit entirely.
 
𝗠𝗼𝗺𝗲𝗻𝘁𝘂𝗺 𝗺𝗮𝘁𝘁𝗲𝗿𝘀 𝗺𝗼𝗿𝗲 𝘁𝗵𝗮𝗻 𝘀𝗽𝗲𝗲𝗱. Once it drops, everything feels harder... because it is.
 
So, how do we fix this issue?

𝗕𝘂𝗶𝗹𝗱 𝗮 𝘀𝘆𝘀𝘁𝗲𝗺 𝘁𝗵𝗮𝘁 𝗿𝗲𝗺𝗼𝘃𝗲𝘀 𝗳𝗿𝗶𝗰𝘁𝗶𝗼𝗻 𝗮𝗻𝗱 𝗿𝗲𝘄𝗮𝗿𝗱𝘀 𝗰𝗼𝗻𝘀𝗶𝘀𝘁𝗲𝗻𝗰𝘆.
 
Systems create predictable results; motivation does not.
 
𝗛𝗲𝗿𝗲 𝗮𝗿𝗲 𝟱 𝗮𝗰𝘁𝗶𝗼𝗻𝗮𝗯𝗹𝗲 𝘀𝘁𝗲𝗽𝘀 𝘁𝗼 𝗵𝗲𝗹𝗽 𝘆𝗼𝘂 𝗴𝗲𝘁 𝘀𝘁𝗮𝗿𝘁𝗲𝗱:

1. 𝗦𝗲𝘁 𝗮 𝗺𝗶𝗻𝗶𝗺𝘂𝗺 𝗱𝗮𝗶𝗹𝘆 𝗰𝗼𝗺𝗺𝗶𝘁𝗺𝗲𝗻𝘁: even 10 minutes keeps the habit alive.
2. 𝗞𝗲𝗲𝗽 𝗮 𝗻𝗼𝘁𝗲𝗯𝗼𝗼𝗸 𝗯𝘆 𝘆𝗼𝘂𝗿 𝗯𝗲𝗱: write down the next task you plan to do - a tutorial, a small feature, fixing some bug, etc. No more guessing what to do next.
3. 𝗧𝗿𝗮𝗰𝗸 𝘆𝗼𝘂𝗿 𝘄𝗶𝗻𝘀: finished lessons, solved bugs, concepts understood. Leave yourself proof of progress.
4. 𝗨𝘀𝗲 𝟭 𝗼𝗿 𝟮 𝗽𝗿𝗼𝗷𝗲𝗰𝘁𝘀 𝗮𝘀 𝘆𝗼𝘂𝗿 𝗹𝗲𝗮𝗿𝗻𝗶𝗻𝗴 𝗲𝗻𝗴𝗶𝗻𝗲 (𝘋𝘔 "𝘴𝘪𝘥𝘦 𝘱𝘳𝘰𝘫𝘦𝘤𝘵" 𝘪𝘧 𝘺𝘰𝘶 𝘸𝘢𝘯𝘵 𝘮𝘺 𝘴𝘪𝘥𝘦 𝘱𝘳𝘰𝘫𝘦𝘤𝘵 𝘤𝘩𝘦𝘢𝘵 𝘴𝘩𝘦𝘦𝘵).
5. 𝗚𝗲𝘁 𝗳𝗲𝗲𝗱𝗯𝗮𝗰𝗸: mentors, peers, or code reviews. Find someone with experience to give you feedback on your code

 
Do this and you’ll 𝗿𝗲𝗯𝘂𝗶𝗹𝗱 𝗺𝗼𝗺𝗲𝗻𝘁𝘂𝗺, 𝗯𝗼𝗼𝘀𝘁 𝗰𝗼𝗻𝗳𝗶𝗱𝗲𝗻𝗰𝗲, 𝗮𝗻𝗱 𝘀𝗺𝗼𝗼𝘁𝗵 𝘆𝗼𝘂𝗿 𝗹𝗲𝗮𝗿𝗻𝗶𝗻𝗴 𝗰𝘂𝗿𝘃𝗲.

Most junior devs don’t realize this: 𝘆𝗼𝘂𝗿 𝘀𝗶𝗱𝗲 𝗽𝗿𝗼𝗷𝗲𝗰𝘁 𝘀𝗮𝘆𝘀 𝗺𝗼𝗿𝗲 𝗮𝗯𝗼𝘂𝘁 𝗵𝗼𝘄 𝘆𝗼𝘂 𝗹𝗲𝗮𝗿𝗻 𝘁𝗵𝗮𝗻 𝘄𝗵𝗮𝘁 𝘆𝗼𝘂 𝗸𝗻𝗼𝘄.
 
The fastest learners aren’t building "simple" projects - they’re building projects that force them into unknown territory.
 
You can grow more from one intentionally over-engineered project than from 10 polished tutorials.
 
𝗪𝗵𝗲𝗻 𝘆𝗼𝘂 𝗱𝗲𝗳𝗮𝘂𝗹𝘁 𝘁𝗼 𝘀𝗮𝗳𝗲 𝘁𝘂𝘁𝗼𝗿𝗶𝗮𝗹𝘀 𝗼𝗿 𝘁𝗶𝗻𝘆 𝗮𝗽𝗽𝘀, 𝘆𝗼𝘂 𝗻𝗲𝘃𝗲𝗿 𝘀𝘁𝗿𝗲𝘁𝗰𝗵 𝘆𝗼𝘂𝗿 𝘀𝗸𝗶𝗹𝗹𝘀.
 
As a result, you never experience the real problems that make you job-ready.
 
The fix:
 
𝗕𝘂𝗶𝗹𝗱 𝗼𝗻𝗲 𝘀𝗶𝗱𝗲 𝗽𝗿𝗼𝗷𝗲𝗰𝘁 𝗯𝗶𝗴 𝗲𝗻𝗼𝘂𝗴𝗵 𝘁𝗼 𝗰𝗵𝗮𝗹𝗹𝗲𝗻𝗴𝗲 𝘆𝗼𝘂 𝗮𝗻𝗱 𝗼𝘃𝗲𝗿-𝗲𝗻𝗴𝗶𝗻𝗲𝗲𝗿 𝗶𝘁 𝗼𝗻 𝗽𝘂𝗿𝗽𝗼𝘀𝗲.
 
Complexity creates a large surface area to learn what you’re missing.
 
Here are 𝟰 𝘀𝘁𝗲𝗽𝘀 𝘁𝗼 𝗵𝗲𝗹𝗽 𝘆𝗼𝘂 𝗴𝗲𝘁 𝘀𝘁𝗮𝗿𝘁𝗲𝗱:

• Choose one project that feels slightly out of your depth.
• Pick a tech stack you 𝘸𝘢𝘯𝘵 to learn, not the one you already know. Use 80% familiar tech and 20% new.
• Add deliberate complexity to one layer (backend, deployment, architecture).
• Treat every blocker as the curriculum - not a reason to quit.
 
Take 30 days to follow this approach and you’ll 𝗯𝘂𝗶𝗹𝗱 𝘀𝗸𝗶𝗹𝗹𝘀 𝘁𝗵𝗮𝘁 𝗻𝗼 𝘁𝘂𝘁𝗼𝗿𝗶𝗮𝗹 𝗰𝗮𝗻 𝗴𝗶𝘃𝗲 𝘆𝗼𝘂.

Are you a “passionate developer”? 
 
Do you need to be? 
 
I've met too many "passionate" developers who:

• have no commits after graduating
• deploy a portfolio site that breaks apart in mobile view
• forgot how to write a for loop

Amber Adamson and I aren't trying to dunk on junior devs. We honestly just want to see you succeed and too much fluff on LinkedIn is designed to make you feel good instead of winning the game.

Link to the episode in comments with some solid ass resources to help you contribute to open source.

Nearly 5 years ago, I made my first 5 figures online by selling interview prep to junior and mid-level developers.
 
Creating that material honestly taught me as much as it helped others.

Let me be clear:
 
Interviewing sucks. This is fax.
 
And yet it’s the highest-paying skill you can have as a developer.
 
If you actually finish the assignments and material I can guarantee you'll be more prepared than 99% of bootcamp grads who are interviewing outside Big Tech.

The program was really successful:

• Ryan got a lead eng position for a well known news org
• Sean went from a chaotic start up to Calendly
• Eric went from PT to FT with a 13K raise
• A young man I met on IG (forget his name) bought a new car after he landed his first role!
 
I'm no longer selling access to this material as I focus on Parsity. 

Instead of letting this material collect dust, I’m giving it away for free until I come to my senses.
 
If it helps even a few people level up then it's worth it (𝘫𝘦𝘦𝘻 𝘐 𝘧𝘦𝘭𝘵 𝘤𝘰𝘳𝘯𝘺 𝘫𝘶𝘴𝘵 𝘵𝘺𝘱𝘪𝘯𝘨 𝘵𝘩𝘢𝘵 𝘣𝘶𝘵 𝘪𝘵'𝘴 𝘵𝘳𝘶𝘦).
 
👉 Grab it here: https://lnkd.in/gmfCB5jm

Stop obsessing over your tech stack.

You can honestly just head to Parsity and grab our syllabus to figure out a safe list of tech to learn.

That's NEVER been the hard part when it comes to learning to code.

To be a hire-able developer, you must build.

All you need is 1 project with 5 stages to take you from HTML to JS to AI to AWS and a whole lot of other acronyms in between ⬇️

𝘐𝘧 𝘱𝘰𝘥𝘴 𝘢𝘳𝘦𝘯'𝘵 𝘺𝘰𝘶𝘳 𝘵𝘩𝘪𝘯𝘨, 𝘫𝘶𝘴𝘵 𝘨𝘳𝘢𝘣 𝘵𝘩𝘦 𝘢𝘳𝘵𝘪𝘤𝘭𝘦 𝘪𝘯 𝘵𝘩𝘦 𝘥𝘦𝘴𝘤𝘳𝘪𝘱𝘵𝘪𝘰𝘯 𝘸𝘪𝘵𝘩 𝘳𝘦𝘴𝘰𝘶𝘳𝘤𝘦𝘴, 𝘣𝘰𝘰𝘬 𝘳𝘦𝘤𝘰𝘴 𝘢𝘯𝘥 𝘦𝘹𝘢𝘤𝘵𝘭𝘺 𝘸𝘩𝘢𝘵 𝘵𝘰 𝘣𝘶𝘪𝘭𝘥 𝘪𝘯 2026.

Open video: The ONLY Project You Need to Build to Become a Software Developer in 2026 - Develop Yourself on buzzsprout.com

The ONLY Project You Need to Build to Become a Software Developer in 2026 - Develop Yourself

Here are 4 services I don't regret buying that no one sponsored me to tell you:

1. https://lnkd.in/guxkUu3e (𝗔𝗹𝗴𝗼𝗘𝘅𝗽𝗲𝗿𝘁) - AlgoExpert is my go to for studying DSA and prepping for FE interviews
2. https://lnkd.in/gc-vexCT (𝗘𝗱𝘂𝗰𝗮𝘁𝗶𝘃𝗲) - Educative's Grokking the Interview exposes the patterns behind 99% of the problems you will encounter in whiteboard interviews
3. https://www.jointaro.com/ (𝗝𝗼𝗶𝗻𝗧𝗮𝗿𝗼)- expert career advice and a true community for developers who want practical guidance
4.  https://codecrafters.io/ (𝗖𝗼𝗱𝗲𝗖𝗿𝗮𝗳𝘁𝗲𝗿𝘀) - you build real software using git to submit your work. For senior devs who are tired of long ass videos (check out John Crickett as well)
5. https://parsity.io/dev30 (𝗗𝗲𝘃 𝟯𝟬) - a 30 day program to learn JS for real and build in public

That 5th one is my own program 😉.

𝗜'𝗺 𝗱𝗼𝗶𝗻𝗴 𝗮𝗻 𝗼𝗹𝗱 𝘀𝗰𝗵𝗼𝗼𝗹 𝗕𝗹𝗮𝗰𝗸 𝗙𝗿𝗶𝗱𝗮𝘆 𝘀𝗮𝗹𝗲 𝘁𝗼𝗱𝗮𝘆. 𝗡𝗼𝗻𝗲 𝗼𝗳 𝘁𝗵𝗮𝘁 𝟭𝟬% 𝗻𝗼𝗻𝘀𝗲𝗻𝘀𝗲. 

Remember this: nearly any course will work for you if you actually go through it. I've used and paid for every resource I listed above and genuinely like them.

Hope that's helpful!

Trivial Business

Providing interim software engineering management (VP Engineering/CTO) for startups and SMEs.
Providing leadership and software development coaching and mentoring to software engineering leaders and their teams.

Example projects:

■ Interim CTO redefining the IT infrastructure and software systems of a business turnaround.
■ Interim CTO of an angel backed start-up.
■ Leading the development of a large scale website for the BBC.
■ Advising on technology strategy for businesses.
■ Advising a consultancy on technology deliver and project turnaround.
■ Advising a technology company on the use of machine learning and NLP to access sentiment on financial news.

Providing training, mentoring and coaching to Staff+ and Engineering Managers on leadership and soft skills.

Providing training, mentoring and coaching software engineers. Delivering the training both on-site and remote. Topics included: Go, Python, C++, NLP and Machine Learning.

Chief Technology Officer

Coding Chats

Podcast Host

Coding Challenges

Writing weekly coding challenges that help software engineers level up by building real-world software applications.

Delivering live software engineering training.

Software Engineering Coach

Acast

Acast is a podcast advertising company. They help creators and advertisers connect.

AWS, CDK, Typescript/JavaScript and node.js

Senior Software Engineering Manager

Met Office

The Met Office is the United Kingdom's national weather service, providing critical weather services and world-leading climate science, helping you make better decisions to stay safe and thrive.

AWS (Cloud) and Python for handling large meteorological data sets.

Contract Software Engineer

Sky is Europe's largest media company and pay-TV broadcaster.

Building serverless solutions to support Sky’s broadcasting activities using Python 3.8, Java, AWS and the Serverless Framework.

Cirrus Logic

Cirrus Logic is a fabless semiconductor supplier that specialises in analog, mixed-signal, and audio DSP integrated circuits.

Managing several teams developing Data Engineering Tools to gather, process and distribute data to support the development, testing and deployment of machine learning algorithms using Python, Conda, PyTest, Numpy, Pandas, Dask and Dask-Distributed.

Starting to build a new team whilst designing, developing and deploying software tools to manage big data for the development and evaluation of biometric algorithms.

Principal Software Architect

Software development for High Performance Computing using Python, SciPy, Pandas, NumPy, Dask, Dask-Distributed and C.

Principal Software Engineer

Morningstar

Morningstar Real-Time Data provides real-time. low latency financial market data feeds.

Leading a globally distributed team of 40+ software engineering and QA staff developing and supporting real time low latency market data feed handlers and supporting infrastructure for several hundred financial exchanges. 
Using C++, C# and Python on Windows.

Head of Software Engineering

Aria Networks

Aria Networks provides artificial intelligence driven network planning and optimisations tools for major telecommunications companies, over-the-top providers and global enterprises.

■ Defining the technical strategy to deliver the business strategy and products.
■ Leading the software development and QA teams delivering a customised network capacity planning and optimisation tool for telecommunications networks (IP, MPLS, OTN, SDN and NFV).
■ Using C++, Boost, QT, JavaScript and Python to build software based around an Artificial Intelligence (AI, specifically Evolutionary Computing/Genetic Algorithms & Neural Networks) 
engine that runs on Windows, Mac and Linux.

VP Engineering

Helping you become a better software engineer through coding challenges that build real applications.

I am on a mission to level up one million software engineers and software engineering leaders!

I’m doing that by: 

1. Helping you improve your coding skills through Coding Challenges that have you building real applications.

2. Helping you improve your software development and soft skills with posts and articles about software development.

You can find the coding challenges here ➡ https://codingchallenges.fyi

You can follow me here on LinkedIn for the posts and articles!

I also post some longer articles on my Developing Skills newsletter here ➡  https://developingskills.substack.com/


My BACKGROUND:

I'm a software engineer and sometimes a manager of software engineers. I've worked as both a senior individual contributor (Staff+) and a senior manager (VP Engineering, Head of Software Development).

I've worked across many tech stacks. I've spent most of the last six years building distributed systems with Python and Flask deployed on AWS using CloudFormation and some CDK. 

Recently there has been some TypeScript/JavaScript, React and Next.js on the frontend with Node.js and Express on the backend. Deployed on AWS using CDK.

For most of my career before that I worked in C++. I'm coming the full circle now and currently learning Rust.

I have a passion to help individuals, teams and departments reach their full potential.

John Crickett

I don’t mind if you let an LLM write all your code, as long as you understand all your code.

Treat it the same way you’d treat a teammate’s pull request. Read it. Question it. Make sure it fits your team’s standards and can be understood by the people who will maintain it.

If it’s good, ship it. If it’s not, refine it or rewrite it. Simple.

AI should accelerate you, not replace your judgement. The quality of your work still depends on how well you can read, reason about, and explain the code you ship.

The rule stays the same: you own what goes to production, no matter who typed it.

CTO / VP Engineering / Head of Software Engineering

Here's my problem with people claiming they use AI to write 13,000 lines of production code per day and who suggest it is a repeatable process.

I can't write a clear enough specification for enough functionality to fill 13,000 lines of code per day, every single day.

And I've never met anyone else who can either.

The bottleneck isn't writing code, it's knowing what code to write.

Let's discuss how we tackle that bottleneck, with or without AI.

19 books on Software Architecture - that you can get for around 4% of the cover price right now!

👉 Modern Software Engineering
👉 Understanding Software Dynamics
👉 Software Requirements Essentials
👉 Righting Software
👉 Balancing Coupling in Software Design
👉 Architecture for Flow
👉 Effective Software Architecture
👉 Software Architecture and Decision-Making
👉 Domain Driven Design Distilled
👉 Functional and Concurrent Programming
👉 Software Architecture in Practice
👉 Practical Object-Oriented Design
👉 Serverless as a Game Changer
👉 The Async-First Playbook
👉 Principles of Web API Design
👉 Strategic Monoliths and Microservices
👉 Domain Storytelling
👉 Continuous Architecture in Practice
👉 Patterns for API Design

You get all of these worth over £618 for around £25 right now through Humble’s Book Bundle and support charity, details here: https://lnkd.in/en2eN_kG

Unskilled and inexperienced software engineers take simple requirements and create complex code.

Skilled and experienced software engineers take complex requirements and create simple code.

The difference is that experience maintaining a complex system, teaches them the benefits of simple code and gives them the skills to do so.

This is also why skilled, experienced software engineers are best positioned to leverage AI-assisted software engineering: they know how to turn a complex set of high level requirements into a simple set of low-level requirements that can be used to prompt and AI-agent and have it build simple code.

Tips for AI-Assisted software development:

If you don’t get it, don’t ship it.

AI can write code fast, but it can’t think about the future. Pasting code you don’t fully understand leads to tech debt, surprises, and skills that get rusty. 

Understanding the code keeps your skills sharp and your product reliable.

Read every bit of code before it hits your repo. If you can’t explain it, rewrite it or prompt the AI to try again.

Want to write better software?

Then embrace the Unix Philosophy as described in The Art of Unix Programming. It provides 17 great rules for writing better software.

With AI-assisted software development rules 1, 2, 5, 6, 7, 8 and 15 are even more important and using AI to generate code satisfies rule 14!

The rules are:

1. Rule of Modularity: Write simple parts connected by clean interfaces.
2. Rule of Clarity: Clarity is better than cleverness.
3. Rule of Composition: Design programs to be connected to other programs.
4. Rule of Separation: Separate policy from mechanism; separate interfaces from engines.
5. Rule of Simplicity: Design for simplicity; add complexity only where you must.
6. Rule of Parsimony: Write a big program only when it is clear by demonstration that nothing else will do.
7. Rule of Transparency: Design for visibility to make inspection and debugging easier.
8. Rule of Robustness: Robustness is the child of transparency and simplicity.
9. Rule of Representation: Fold knowledge into data so program logic can be stupid and robust.
10. Rule of Least Surprise: In interface design, always do the least surprising thing.
11. Rule of Silence: When a program has nothing surprising to say, it should say nothing.
12. Rule of Repair: When you must fail, fail noisily and as soon as possible.
13. Rule of Economy: Programmer time is expensive; conserve it in preference to machine time.
14. Rule of Generation: Avoid hand-hacking; write programs to write programs when you can.
15. Rule of Optimization: Prototype before polishing. Get it working before you optimize it.
16. Rule of Diversity: Distrust all claims for “one true way”.
17. Rule of Extensibility: Design for the future, because it will be here sooner than you think.

Embrace the UNIX Philosophy

Tips for AI-assisted software development:

Boring tech gives AI superpowers.

AI coding agents performs best with tools, languages, and frameworks that have been around long enough to show up consistently in its training data. 

When you push it onto the bleeding edge, it starts hallucinating, and the quality drops. You’ll see odd patterns, missing steps, or advice that just doesn’t hold up.

To get the best results, pick a well-established framework or language. Pick 'boring' tech! Ten tell the AI exactly what you’re using.

Tips for AI-Assisted software development:

Don't ask AI to build the house, ask it to make the bricks.

People struggle with AI coding tools because they're asking for too much at once. They want entire features, complete apps, full systems. The AI generates something massive, half of it doesn't work, and now you're debugging spaghetti code you didn't write.

Flip the approach. Ask AI to generate small, well-defined components. A single function. A reusable component. One API endpoint. You architect how they fit together.

Think LEGO, not construction. AI is incredible at fabricating pieces to spec. 

You're still the one building something meaningful from them.

29 great books on AI Algorithms and LLMs - that you can get for around 3% of the cover price right now!

This looks like a great deal, in particular I recommend Emmanuel Maggiori’s book: The AI Pocket Book. I'm looking forward to reading several others!

👉 Build A Large Language Model
👉 AI Agents In Action
👉 Grokking Artificial Intelligence Algorithms
👉 AI-Powered Search
👉 Generative AI In Action
👉 AI For Everyday IT
👉 Causal AI
👉 The Art of AI Product Development
👉 Starting Data Analytics with Generative AI and Python
👉 Learn AI-Assisted Python Programming
👉 AI as a Service
👉 Interpretable AI
👉 Software Testing with Generative AI
👉 Learn Generative AI With PyTorch
👉 Time Series Forecasting Using Foundation Models
👉 Effective Conversational AI
👉 How Large Language Models Work
👉 Succeeding With AI
👉 Introduction to Generative AI
👉 AI-Powered Developer
👉 Inside AI
👉 Build Financial Software With Generative AI
👉 Data Storytelling With Altair and AI
👉 Coding With AI
👉 Prompt Engineering For AI Systems
👉 Zero To AI
👉 The Complete Obsolete Guide to Generative AI
👉 The AI Pocket Book
👉 Regular Expression Puzzled and AI Coding Assistants

You get all of these worth over £1155 for around £35 right now through Humble’s Book Bundle and support charity, details here: https://lnkd.in/eAwEJAiu

What if that unrealistic estimate isn't wrong? What if you just don't know why it might be right?

Your manager says hours. You're thinking days. They must be stupid or unreasonable, right?

Maybe. Or maybe they know something you don't. A tool. A technique. Some context that changes everything.

You won't find out by complaining. You will find out by being curious. Ask them: "How do you see this getting done in that time?"

Two things happen. Either you learn something that makes you faster, or they realise they missed something and you have a real conversation about time or scope.

Either way, you win.

taplio

The Battle

Brian Jenney

John Crickett

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taplio

The Battle

Brian Jenney

John Crickett

Followers

Posts

Engagements

Likes

Performance Score.css-goub6s{font-size:var(--chakra-fontSizes-md);font-weight:500;color:var(--chakra-colors-gray-600);display:block;margin-top:var(--chakra-space-1);}Brian Jenney's LinkedIn Performance

Performance ScoreJohn Crickett's LinkedIn Performance

Ready to grow your LinkedIn presence?

Performance ScoreBrian Jenney's LinkedIn Performance