---
meeting: Enterprise Brain Scrum
date: 2026-04-05
participants:
  - Yeshwanth Reddy Yerraguntla
  - Rajashekar G
duration: ~10:00
transcript: 20260405.txt
---

# Enterprise Brain Scrum — April 5, 2026

A weekend status scrum covering data refinement work, visualization development, deployment verification, and priority planning for the sprint. The meeting emphasized the urgent need to start on Promptfoo evaluation, UI agent development, and training lifecycle implementation with hard deadlines approaching.

## Act I - Data and Visualization Progress (~00:08:05 - ~00:10:40)

Rajashekar walked through the weekend's accomplishments. The team reworked the data sheet, filled gaps through discussions, and documented remaining issues. They converted the work into proper JSON format for the system.

Using the Vasa documents on Invictus data, Rajashekar developed business context and injected it into the system. Visualization gaps were addressed—previously missing line graphs were finalized. The system was deployed Friday night and needs testing now.

> _"we have deployed yesterday night and deploy we need to test these two"_
> — Rajashekar G _(~00:09:20)_

The second part: new visualizations from the design team. These aren't Plotly-based—they're custom components. Amulya will work on integrating those today.

Rajashekar raised the resource allocation question: should he keep one person dedicated to testing? Yeshwanth immediately redirected: yes, but more critically, they need someone dedicated to Promptfoo evaluation work—suggesting Harshit.

The other major pieces for this sprint: UI agent and training lifecycle. Yeshwanth noted one week is already gone from the sprint.

## Act II - Minimum Viable Training Lifecycle (~00:10:40 - ~00:12:00)

Yeshwanth pushed for immediate action on the training lifecycle with a clear directive: start with minimum viable product today. The target: generate basic code demonstrating the system is learning, using mock data only.

> _"Start with the minimum product now like whatever it takes you generate a basic code which demonstrate that it is working with mock data okay your target should be only that one thing by end of the day"_
> — Yeshwanth Reddy Yerraguntla _(~00:10:40)_

The bar is deliberately low for the first pass: launch the command, ask a question, see the change in the database (or system prompt) proving learning occurred. System prompt modification is acceptable.

> _"aim for today just that you launch this command you ask this question this changes in the database because it is learning yeah system prompt is also fine"_
> — Yeshwanth Reddy Yerraguntla _(~00:10:40)_

Yeshwanth acknowledged coordination overhead is consuming Rajashekar's time, but as the leader, he must still deliver this. The implementation path: extract system prompt to a text file, make Python load it, provide an editing mechanism, and demonstrate the learning workflow.

The urgency: if they can't demonstrate this today, there won't be time in the next four days to clean it up for delivery.

Rajashekar mentioned something about a call regarding the Infinithesim agent—Wernut called Saturday asking to link the Infinithesim database with Enterprise Brain. (Audio quality degraded at this point, making details unclear.)

## Todos

- [ ] Complete testing of Friday night deployment (data refinement and visualization updates) | author: Rajashekar G, Team | deadline: 2026-04-05
- [ ] Integrate design team's custom visualization components (non-Plotly) | author: Amulya | deadline: 2026-04-05
- [ ] Assign dedicated resource to Promptfoo evaluation work | author: Harshit | deadline: 2026-04-05
- [ ] Demonstrate minimum viable training lifecycle POC (system prompt learning) by EOD | author: Rajashekar G | deadline: 2026-04-05
- [ ] Clarify Infinithesim database integration requirements from weekend call | author: Rajashekar G | deadline: 2026-04-06