Fernando Giancoli | Building Pairloom

Building Pairloom — the collaboration layer for teams using AI coding agents.

Keep context, decisions, and handoffs connected across agents.

Solo founder

[Fernando Giancoli | Building Pairloom @dropmetrics]

Unpopular opinion:

Giving 5 AI agents access to the same codebase doesn’t make you 5x more productive.

Sometimes it just means 5 agents creating 5 different problems.

[Fernando Giancoli | Building Pairloom @dropmetrics]

@_LouiePeters At what point does keeping one massive session alive become worse than starting fresh? Is there a reliable signal that the context has become too stale?

[Fernando Giancoli | Building Pairloom @dropmetrics]

@hnshah @JoshuaEbner When you have several agents working in parallel, what's the hardest thing to keep synchronized: task status, shared context, code changes, or review?

[Fernando Giancoli | Building Pairloom @dropmetrics]

@stretchcloud Curious how you handle conflicts when two different agents request permission for actions that affect the same project. Is there a shared approval process?

[Fernando Giancoli | Building Pairloom @dropmetrics]

@KOF97AI How do you handle it when the implementer discovers something that changes the original plan? Does that go back to the planner, or does the handoff document become the source of truth?

[Fernando Giancoli | Building Pairloom @dropmetrics]

@addyosmani The interesting shift is that coding is becoming the easy part. Keeping multiple agents aligned and verifying their work is becoming the actual job.

[Fernando Giancoli | Building Pairloom @dropmetrics]

@maomao000211 @smartmemoryai How do you currently keep track of decisions that change over time when multiple agents are working on the same codebase? Do you use a shared log, Git commits, documentation, or something else?

[Fernando Giancoli | Building Pairloom @dropmetrics]

Most AI coding agent handoffs are missing something important.

They explain what changed, but not why it changed.

If you're switching between Claude Code and Codex, here's what I'd preserve in every handoff 🧵

[Fernando Giancoli | Building Pairloom @dropmetrics]

@MitcheIl 14 wasn't even an option.. guess I have to make my own category

[Fernando Giancoli | Building Pairloom @dropmetrics]

How about for 14???

[Mitchell @MitcheIl]

Who's the biggest founder your age?

The founders of the most valuable companies, ages 19 to 55:

[Fernando Giancoli | Building Pairloom @dropmetrics]

@smartmemoryai @maomao000211 That's interesting. Do you maintain a shared decision log that agents read before starting, or does each handoff generate and update it? I'm curious how you prevent it from becoming outdated.

[Fernando Giancoli | Building Pairloom @dropmetrics]

Your AI agent shouldn't have to rediscover what the last one already learned.

Decisions, failed attempts, and the WHY matter more than a list of changed files.

That's the context AI coding is missing.

[Fernando Giancoli | Building Pairloom @dropmetrics]

@HCStudio84 That’s a good point. A handoff should preserve not just what worked and why, but what was tried, what failed, and why it was rejected. Otherwise the next agent can waste tokens repeating the same dead ends. Definitely something worth including.

[Fernando Giancoli | Building Pairloom @dropmetrics]

Building Pairloom has taught me something:

AI agents need more than instructions. They need context.

Especially the why behind decisions, so the next agent doesn’t undo intentional work.

That’s what I’m trying to solve.

[Fernando Giancoli | Building Pairloom @dropmetrics]

@maomao000211 Exactly. The next agent can see what changed, but without the reasoning it has no way to know which decisions were intentional. That’s the context I’m trying to preserve with Pairloom.

[Fernando Giancoli | Building Pairloom @dropmetrics]

@Fahadh_4444 I’m aiming to have the agent draft it before switching, then let the developer review and approve it. The important part is preserving the reasoning, decisions, and unfinished work — not just generating a summary of changed files.

[Fernando Giancoli | Building Pairloom @dropmetrics]

5/5 — A reusable handoff checklist

Before switching agents, ask:

Does it know the original objective?

Does it understand the important decisions?

Can it distinguish verified facts from assumptions?

Does it have a concrete next action?
https://t.co/JtEScsfAq3 helps throughout

[Fernando Giancoli | Building Pairloom @dropmetrics]

4/5 — What's next?

Give the next agent a specific starting point.

Not "continue building."

Instead: "Implement the refresh-token endpoint in server/auth/session.ts, add expiration tests, and verify existing sessions still work."

[Fernando Giancoli | Building Pairloom @dropmetrics]

3/5 — Actual progress

Separate completed work from unfinished work.

Include:

Files changed

Features implemented

Tests actually run

Test results

Known bugs and blockers

Never report a test as passing if it wasn't run.

[Fernando Giancoli | Building Pairloom @dropmetrics]

2/5 — Decisions

Record:

What approach was chosen

Why it was chosen

What alternatives were rejected

Any constraints that influenced the decision

This prevents the next agent from repeating the same investigation.

[Fernando Giancoli | Building Pairloom @dropmetrics]

1/5 — The objective

What was the agent actually trying to accomplish?

Include the original task and the expected outcome. Don't make the next agent reconstruct the goal from code.