Co-founder and CEO at Bito. 

We build codebase intelligence for AI coding and reviews, so AI tools can reason about real systems instead of guessing. 

Before Bito, I built and scaled companies across multiple markets, including PubMatic (NASDAQ: PUBM). 

Right now, I spend most of my time thinking about AI, software systems, and why understanding codebases matters more than writing code faster.

Amar Goel

Your coding agent indexed your entire codebase and still has no idea how your services connect. Cursor, Claude Code, Copilot. 

They all build symbol tables, follow references, create searchable indexes when you connect your repos. Fast, accurate file lookup. And for scoped, single file edits, that genuinely works.

The problem shows up the moment work crosses service boundaries.

Your agent can find a file. It cannot tell you why a safeguard was added after a production incident, or which downstream consumers break if you change a schema. 

That knowledge lives in the relationships between code, and indexing does not capture relationships.

We keep seeing this pattern with teams of every size. 

They assume indexing solves the context problem, then spend weeks debugging agent output that looked right but missed the system entirely.

We wrote about why this keeps happening and what actually closes the gap.

Read here:

Bito | Top score on SWE-Bench Pro - Deep codebase intelligence for AI coding and reviews

Open article: Why Coding Agents Get Lost in Your Codebase (Even After Indexing Everything)  by bito.ai

Why Coding Agents Get Lost in Your Codebase (Even After Indexing Everything) 

Anand Chandrasekaran ⚡️

I am helping build Crescendo AI and HiOctave AI (Founder) and Celesta Capital (Managing Partner). Formerly, as Partner @ General Catalyst, I helped establish the India-US investing practice and co-create Crescendo, an early offshoot of the Applied AI rollups practice.

Before that, I was CPO/product leader with an overarching mission of democratizing technology platforms - at Five9, we grew from $120m ARR to over $600m bringing CX to cloud and multiple channels through Covid. At Meta (Messenger Platform), we established and grew ‘people to business’ use cases globally for > 1 billion monthly users. At Bharti Airtel, we transitioned from a voice to a data-first network for 300m subscribers in India. Snapdeal / FreeCharge was a roller coaster experience bringing eCommerce to first time consumers and integrating payments.

I enjoy partnering with commercially minded & product obsessive builders. Was an early investor in 80+ companies since 2016 of which 10 today are valued > $1 billion including Deel, OneCard, NoBroker, Hippocratic, PIPE, Carta, Dealshare etc. and 25 more between $100M-1B including InVideo, Titan MSP, MoEngage, Jeh Aerospace, Monarch Money, Exotel, Orange Health, Tonetag, Beacon.ai, Loop, Two Chairs, Farmart, Smith.ai, Observe.ai etc. Named top seed investor focused on 🇮🇳/🇺🇸 by HURUN India Report 4 years in a row (2022-25). Learned a lot co-founding/building Aeroprise fresh out of Stanford (acq by BMC Software).

I hold an M.S. in Electrical Engg. from Stanford University, and a B.S. from PSG College of Tech, India. Part of Young Global Leader community @ World Economic Forum, Fortune's 40 under 40 etc.

Partner

Something big is happening in CX. Tod Famous and I cover how at Crescendo we are moving from workflows and pseudocode to true autonomy (paired with decision traces and recursive self-improvement). 

We foresee hyperbolic improvements in call center automation.

Andy Lee | Matt Price | Slava Zhakov | Slava Sayko 
General Catalyst | Celesta Capital

Anand Chandrasekaran

Managing Partner, Celesta Capital and Founder of Crescendo & HiOctave || Former Partner @ GC, 80+ seed investments, 10🦄s || Product @ Meta/Airtel/Five9.

Chief Product Officer Crescendo | Technology Executive | GenAI | CX expert

Stop building workflows.

And stop rewriting them in prompts and calling them "agentic".

The Agentic loop is reshaping how AI systems operate — autonomy paired with instrumentation and decision traces is unlocking recursive self improvement. 🚀 

Anand Chandrasekaran and I share our thoughts on what's happening in CX.  Crescendo

By Anand Chandrasekaran and Tod Famous This article was co-authored by Anand Chandrasekaran, Co-founders of Crescendo AI. What follows is a perspectiv

Open article: From Workflows to Agentic AI by Tod Famous • 5 min read

Most CX leaders aren’t failing at AI; they’re just missing a shared definition of progress.

Without a clear model, AI investments turn into disconnected pilots, inflated expectations, and unclear ROI. The real challenge isn’t whether to use AI, but how maturity actually develops over time in the contact center.

That’s the thinking behind the Crescendo AI Maturity Model: a practical way to understand where AI creates leverage, where it breaks down, and what capabilities matter at each stage. We’ve seen similar models help drive progress in other industries including in self-driving cars. 

If you’re serious about scaling AI in CX and not just experimenting forever, this framework is worth your time.📘 

https://lnkd.in/gvf3fVKe

Andy Lee | Matt Price | Slava Zhakov | Tod Famous

Managing Partner, Celesta Capital and Founder of Crescendo & HiOctave || Former Partner @ GC, 80+ angel investments, 10🦄s || Product @ Meta/Airtel/Five9.

AI isn’t underperforming in contact centers because the technology is weak. It’s underperforming because it’s layered onto systems built for another era.

Billions have been invested. Yet most CX teams still feel stuck, juggling tools, chasing metrics, and struggling to scale real outcomes. That gap between automation potential and operational reality is what we call the AI Performance Gap.

In our AI Maturity Model for Contact Centers, we outline what real progress looks like, and how organizations move from fragmented automation to AI-native operations where people and AI work as one system. 🤝

When AI is built into the core of CX, outcomes compound. Costs drop. Speed increases. Empathy scales. 🚀

Learn more: https://lnkd.in/ekNUBD_r

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