# Minutes of Meeting - Enterprise Brain
**Date:** February 23, 2026  
**Source transcripts:** [Feb 23, 2026.txt](Feb%2023,%202026.txt), [Feb 23, 2026-2.txt](Feb%2023,%202026-2.txt), [Feb 23, 2026-3.txt](Feb%2023,%202026-3.txt)

The meeting unfolded in order, not by topic: first the Tata Steel pitch, then the product slice, then the deeper agent architecture, and finally the execution plan. The deadline pressure was a Wednesday presentation, but the larger shift was that the team stopped talking about a chatbot and started talking about orchestrated source agents and proactive intelligence.

## Act I - Tata Steel framing and terminology reset (00:00 – 08:17)

Venkatesh opened by separating the Tata Steel ask from the broader internal platform work. He did not want an AI-first UI pitch; he wanted a business presentation that explains what Enterprise Brain is, how it works, and why Tata Steel should trust it.

> *"I want all of us to change the terminologies."*
> — Venkatesh Tammareddy _(~00:08:17)_

The first phase was intentionally narrow. Venkatesh framed it as NLP search, vendor comparison, and event-triggered snippets so the product can show useful intelligence before the user even asks. The presentation itself became a two-layer deliverable: a business story for the customer and a technical story for the team.

> *"we are working in phases right now they don't need an AI first product all I need is NLP search"*
> — Venkatesh Tammareddy _(~00:05:32)_

## Act II - The first product slice and business story (08:17 – 11:12)

The next stretch turned the Tata Steel ask into a concrete pitch structure. The team discussed showing quoted price comparisons, quote triggers, and side-panel intelligence so the system can feel alive even before the full platform exists.

At this point the meeting was still about the external deliverable, but the design constraint was already visible: don’t oversell a UI trick, and don’t turn the pitch into an AI-first architecture claim. The first business story had to be simple enough to explain and strong enough to survive customer scrutiny.

## Act III - Agents and the operating model (11:12 – 24:10)

The architecture conversation then moved into the shape of the system. Across the transcripts, the group converged on the same pattern: each source gets its own agent, each agent knows its source-specific entities and priorities, and a central layer correlates the results.

The important distinction was that data source agents are not just retrieval wrappers. They need to publish metadata about entities, frequency of change, priority, and source-specific meaning so the central brain can decide when to pull, what to store, and when to escalate.

> *"It has to learn new skills on the fly."*
> — Naveen Puttagunta _(~00:24:10)_

The refresh schedule became a first-class object in this conversation. Some parts could be hardcoded at first, but the long-term direction was clear: make refresh configurable, then agent-driven, so the system can keep its own view of the organization current.

## Act IV - Proactiveness, refresh, and personalization (24:10 – 35:00)

The next pivot was around proactiveness. The system should not wait for the user to ask the right question; it should refresh on a cadence, compare against the previous snapshot, and push meaningful changes to the right person.

That led into user personalization. Different people care about different slices of the same project, so the same source update should not land the same way for everyone. The point was not just “alerting”; it was role-aware and preference-aware surfacing.

## Act V - Backlog, ownership, and weekly discipline (35:00 – end)

The final part of the meeting shifted from architecture to execution discipline. Venkatesh wanted the architecture translated into a backlog, not just discussed. The team also needed ownership around who would maintain the roadmap, who would drive the Tata Steel materials, and who would keep the cadence moving so the same issues did not get re-litigated every few days.

By the end, the meeting was no longer about whether Enterprise Brain could be explained. It was about whether the team could convert the explanation into a working plan: a presentation, a backlog, a refresh model, and an explicit source-agent contract.

## Todos

<todo>Prepare the Tata Steel business presentation with architecture, AI governance, security, and ops framing<br/><span class="owner">Venkatesh / Satyasri / Yeshwanth</span> <span class="deadline">Feb 25, 2026</span></todo>
<todo>Convert the architecture discussion into an implementable backlog and task split for the team<br/><span class="owner">Yeshwanth / Rajashekar / Manisha</span> <span class="deadline">Next working session</span></todo>
<todo>Define the metadata every agent must publish, including entities, priorities, refresh cadence, skills, and user preferences<br/><span class="owner">Naveen / Gopal / Yeshwanth</span> <span class="deadline">Next working session</span></todo>
<todo>Keep the working cadence daily so architecture decisions and backlog items stay synchronized<br/><span class="owner">Prabhakar / team leads</span> <span class="deadline">Ongoing</span></todo>