ZeroShot by BuildBetterZeroShotby BuildBetter
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Evidence-based coding

Every customer signal,
in your agent’s hands.

One shared repository of everything your team and its agents know — piped back into every spec, review, and PR so the loop actually closes.

One shared repository

Stop paying twice
for the same context.

Every session — chat, file edits, tool calls — is saved and shared across your whole team. Check out an old branch and pull up the chat that produced it. Resume a teammate’s session on your machine. No agent ever pays tokens to rediscover what someone already figured out.

  • → Sessions synced across repo, branch, PR, commit, and teammate
  • → Resume any teammate’s session with one command
  • → Switch Claude Code → Codex mid-task, same memory
resume — 6mo old branch
$ bb agent-sessions resume
? Resume which session?
❯ auth/oauth-rewrite · spencer · 6mo ago
payments/stripe-webhook · nikhil · 4mo ago
✓ Hydrating session 1f2c8d — 312 messages, 28 file edits
Codex › This is the OAuth rewrite from June.
The blocker was the refresh-token race in the worker queue.
Same question. Different answer.

The same question.
A radically different answer.

Same agent, same PR, same teammate’s work. The difference is whether it can pull the session that produced the code — or has to burn tokens re-deriving it from scratch.

coding-assistant.ai
What was Spencer trying to accomplish with the LLM data source PR (#3308)?
$ gh pr view 3308 --json title,body $ git diff main...HEAD
It adds an exec plan to ingest LLM chats into the signal pipeline. The PR description is sparse — let me read the whole implementation.
why is he using the conversation model? was that intentional?
I don’t have visibility into Spencer’s reasoning. Want me to guess?
forget it — write a spec for the export feature. start with what customers asked for
I don’t have access to your customer signals or tickets. I can write something generic — want me to make assumptions?
forget it. just review the PR.
Reviewing for syntax and obvious bugs. I can’t compare against your team’s conventions — no prior reviews to reference.
six months later
customer ticket #4127 — agent logs aren’t showing up in reports. why did we structure agent_logs this way?
$ git log --all --oneline src/agent_logs
27 commits across 4 contributors. PR descriptions don’t mention reporting trade-offs.
who owns this if we change it?
I can’t tell from git blame alone. You’d have to track down each contributor and ask.
Starts from zero every time — and burns tokens re-deriving what someone already knew.
›_
coding-assistant + ZeroShot CLI
Context loaded
What was Spencer trying to accomplish with the LLM data source PR (#3308)?
✓ Found Spencer’s Codex session on this branch — 247 messages. Pulling context (0 tokens spent re-deriving it).
spencer’s session · PR #3308

• Goal: ingest LLM chat history as a new signal source

• Decision: reused conversation as a placeholder — wants to migrate to agent_logs

• Open Q for Nikhil: “should agent_logs be its own model? need your call before I split it.”

draft my review with /bb-review
✓ Posted to PR #3308. Three suggestions, all citing your team’s prior conventions on the conversation table.
six months later
customer ticket #4127 — agent logs aren’t showing up in reports. pull context.
✓ Found 14 sessions across 6 months tied to agent_logs. Pulling project history.
project history · agent_logs

• Mar ’26 · spencer scoped initial schema (PR #3308)

• Apr ’26 · maya denormalized for streaming reports “to keep queries under 50ms” (PR #408)

• Aug ’26 · daniel added session_type column (PR #1547)

✓ The structure is intentional. Ticket #4127 is missing an index on session_type from Daniel’s August change. Draft /bb-specify for the migration?
yes
✓ Spec drafted. Clustered #4127 with 7 other customers on slow exports and pulled their quotes — then /bb-plan and /bb-tasks queued the migration.
/trust-but-verify before merge
✓ Walked the export flow end-to-end. 4 customer-cited paths pass, 0 regressions on the existing reports.
ship it
✓ PR #2089 merged. The 8 customers who reported it were notified automatically.
✓ Heads up — your team re-flagged this session_type index convention 3× this quarter. Opened a weekly skill PR so your agents catch it next time.
Six months ago, six minutes ago — same context, zero tokens to rebuild it.
Same story, everywhere you work

Every job is cheaper with the context.

Onboarding, debugging, scoping, reviewing — the same question costs a fraction of the tokens when your agent can pull the work that came before. Each card shows the skills it leans on.

Onboard a new engineer
“Why is the payments module built this way?”
✗Reads the code blind and pings four people on Slack.
✓Pulls the original sessions and the decisions behind them.
bb agent-sessions resume/bb-analyze
Debug a production incident
“Ticket #4127 — exports failing for big orgs.”
✗git blame archaeology across 27 commits, 4 authors.
✓Surfaces 14 related sessions and the exact missing index.
/bb-specify/trust-but-verify
Scope from customer feedback
“Spec the CSV export fix.”
✗Writes something generic on made-up assumptions.
✓Clusters 8 customer tickets into a spec with real quotes.
/bb-specify/bb-clarify
Review to your conventions
“Review PR #3308.”
✗Flags syntax and obvious bugs only.
✓Cites your team’s prior calls on the conversation table.
/bb-review
Resume half-finished work
“Pick up the OAuth rewrite from June.”
✗Starts from zero and re-derives the whole plan.
✓Hydrates the 312-message session and the open blocker.
bb agent-sessions resume
Never repeat a mistake
“Add a retry to the worker queue.”
✗Invents a brand-new retry abstraction — again.
✓Reuses RetryablePolicy, the convention set in PR #408.
/bb-review/payments-review
Close the loop

A ticket in the morning.
A PR by end of day.

A ticket comes in. ZeroShot clusters it with the other customers who hit the same thing,/bb-specify pulls those quotes into a spec,/bb-review checks your conventions, and the PR ships.

Customer signals
CallTicketSurveySlackFeedbackCRMEvent
From your agents (via CLI)
CommitChat sessionSteering eventsProject context
BuildBetter AI
Paid platform
Signal Generation
Signals
SeverityTopicPersonaImpactKeywordsSegmentation
Triage / Projects
TopicsClustersProjectsKnowledge baseCompany context
›_
ZeroShot CLI — captures your work and runs the workflow
Free
Runs the spec workflow
/bb-specify→/bb-plan→/bb-tasks→/bb-review→/trust-but-verify
Across your coding agents
Claude CodeCodexCopilot CLIGemini CLIWindsurfAmazon Q
Then, on the platformMetered
Extracts signals from your sessions
repeated patternswasted tool callsconventionsseveritytopic
Suggests & ships skills
find patterns→write / sharpen skill→weekly skill PR
Metered by tool call.You only pay for the signal extraction, skill suggestions, and skill runs you actually use — the CLI and open-source skills stay free.
← Close the loop — customer notified, feedback restarts the cycle →
Ship at the speed of insight

A customer ticket, end-to-end. Same day.

9:14am
Ticket #4127
Export CSV failing for orgs > 10k rows
9:32am
Signal clustered
+ 7 prior tickets · Enterprise · High severity
10:48am
/bb-specify
Spec drafted with 8 customer quotes
2:15pm
/bb-review
passes · PR #2089 merged
4:42pm
8 customers notified
Loop closed.
The full pipeline, end to end

Every stage of the loop — and the skills that run it.

From capturing the work to shipping the PR to learning from it — the whole thing runs inside the CLI, and feeds back on itself so the library compounds.

›_
Inside the CLI — the full workflow
  1. 1
    Capture

    Every session, commit, steering event, file edit, and tool call — synced into one shared repo across your whole team.

  2. 2
    Scope/bb-specify/bb-clarify/bb-constitution

    Turn customer signals into a spec, resolve the unknowns before you build, and encode your team’s principles.

  3. 3
    Plan/bb-plan/bb-tasks/bb-analyze

    Break the spec into a build plan and a dependency-ordered task list — checked for cross-artifact consistency.

  4. 4
    Build/bb-implement

    Execute the plan task by task — in whichever agent you’re already using, with the full context loaded.

  5. 5
    Verify/bb-review/trust-but-verify/generate-tests/bb-checklist

    Review against your conventions, walk the UI like a real user, generate tests, and run the pre-merge checklist.

  6. 6
    Ship

    The PR merges. The customers who reported it hear back — same day, not next quarter.

  7. 7
    Learnweekly skill PR

    Signals run over the sessions, identify the patterns your team keeps repeating, and open a weekly PR with new and sharper skills.

↻ Learn feeds back into Scope — the library compounds, and every loop costs fewer tokens than the last.
A new data type

Agent sessions are
the new call recording.

Every chat your team has with an agent is company knowledge — prompts, decisions, conventions — that’s lost the moment the window closes. ZeroShot captures it as a first-class data type.

Prompt library
Brand voice42 uses
Marketing copy28 uses
Image generation19 uses
PR description63 uses

The prompts your team already wrote — pulled out of chat sessions, shared, reused.

Extractions & insights
DecisionReuse RetryablePolicy
BlockerRefresh-token race in worker
Conventionagent_logs, not conversation
Open QSplit agent_logs model?

Signals run over every session — decisions, blockers, and conventions, structured.

Artifacts created for you
OAuth rewrite — design doc
updated 2h ago
Signal pipeline — runbook
updated 1d ago
agent_logs — schema notes
updated 3d ago

Knowledge docs your agents wrote — yours to view, edit, and share. Delete ZeroShot, lose it all.

Prototype, don’t rebuild

Ten variants for the
price of one build.

Spin up front-end prototypes as HTML mockups — explore ten directions before you wire a single endpoint. Pick the winner, then build it once. A quarter of the tokens, none of the throwaway backends.

  • → Generate variants in ZeroShot, not your agent’s token budget
  • → Compare side by side, ship the one that works
  • → Build the real thing once you’ve settled the design
Dashboard — 4 variants¼ the tokens
Variant A
Variant Bshipped
Variant C
Variant D
“Whether extreme spend pays off comes down to the business value of shipped code — which most companies still can’t measure.”
Nicholas Arcolano
Head of Research, Jellyfish
TechCrunch →

Get twice as far on the same budget.

Install once. Your agents inherit your team’s skills, your sessions stay shared, and your token spend drops. 30-day free trial — no card required.

$ curl -fsSL buildbetter.sh | sh

Or view on GitHub