Capture. Understand. Compound.

Codiedev captures the ground truth of AI work: every session, the full prompt and response, across every tool and every team. It turns each one into a readable story, and feeds what it learns back into the work. Here's the whole loop, end to end.

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Insight up, improvement down.

Sessions flow in from everywhere AI is working. Insight flows up to leaders. Improvement flows back down into every session that follows.

Connect your team in minutes

Developers' coding agents and Claude Cowork across the business. No months-long implementation, no consultants.

Every session captured and understood

The ground truth — the full prompt and response — categorized and summarized into a story: problem, approach, tools used, lessons learned.

Insight up, improvement back down

Cited reports and observations for leaders. Skills and context injected automatically for teams.

Every session becomes a story anyone can read.

Raw transcripts are unreadable at scale. Codiedev summarizes each session into the problem, the approach, the tools used, and the lessons learned, tied to the ticket and the pull request it shipped in. Insight takes seconds, not log-diving.

Tied to the work. Each story links to the ticket it served and the PR it produced, so the record connects intent to outcome.

Categorized. Building, fixing, investigating, refactoring, plus the tools and models used, for every session.

Lessons kept. What the session learned is extracted and kept, becoming the raw material for skills and shared context.

Session story

Sample session · annotated · illustrative data

Made webhook ingestion idempotent with retry and backoff

Problem

Events dropped under load; the consumer acked before processing. Raised in PAY-311.

Approach

Moved the ack after commit, keyed retries to event IDs, added exponential backoff. Verified against the replayed event log.

Tools used

Claude Code queue/consumer.ts replay harness

Outcome

Shipped in PR #482. Zero dropped events since.

Lesson learned

Ack-after-commit is now the team pattern for every consumer, captured as a skill the same day.

What one session learns, every session inherits.

The more your team works with AI, the better every session gets. Lessons become skills that apply themselves, so nobody has to remember to ask. Context compounds, so every session starts with what the team already learned. And every skill shows its own effect: how often it fires in live sessions and how much shipped work it touched, from Seeding to Spreading to Compounding.

Dashboards report on last sprint. Codiedev improves the next session.

The engineering record, at session-level resolution.

Sessions tied to tickets and PRs. Follow any piece of work from intent to merge: what was asked, what the AI did, what shipped.

Tool and model comparison. See what the same work costs and yields across AI tools and models, and where switching or blending would pay.

Cost per unit of output. The true cost to ship, per merge or per feature, trending over time. Not a lump-sum bill.

Waste, eliminated. Spot spend on work that never shipped, and the dead ends a shared skill would have avoided.

CostModelsRepos

Fully-loaded cost per merge

AI spend + time, per shipped merge

8 weeks

$4.49/ merge · trending down

Same work on other models · per merge

Gemini 2.5 Pro$1.78

Claude Sonnet 4.648% in use$2.69

Claude Opus 4.852% in use$4.49

Illustrative sample data: switch or blend models to cut cost.

Recent sessions · tied to work

PAY-311webhook idempotencyPR #482

BILL-475timestamp migrationPR #491

CORE-208cache-refresh hooksin review

Real velocity

How fast work actually ships, measured from sessions, not story points.

Bottlenecks, surfaced

Where work stalls between intent and merge, visible while there's still time to act.

Predictability

Estimates re-anchored to where work actually lands now.

The same lens, on every AI-assisted role.

Claude Cowork sessions are captured and understood the same way, so the ground truth of your AI transformation covers the whole company, not just the engineering org.

Legal

Contract review, remembered

Redlines against the negotiation playbook, captured as sessions, so the playbook itself gets better with every contract.

Finance

Models with a paper trail

Variance models and close analysis built with AI, each session a documented, citable record of how the number was reached.

Ops & marketing

Process knowledge that compounds

Vendor triage, campaign analysis, runbooks: the lessons from each session flow into shared context for the next person.

The numbers behind the AI line item, defensible for the first time.

Budget burn-down with run-rate projection. See the overrun coming before the bill arrives. The projection turns red before month-end, not after.

Fully-loaded cost per merge. A board-slide number, trending down as AI lifts throughput.

CapEx classification from sessions. AI work auto-classified into an investment taxonomy with capitalizable flags, lockable reporting periods, and an audit trail. Metadata tools can't capitalize what they can't see.

Waste eliminated, in dollars. Hours and labor-dollars saved because a shared skill already had the answer: the dollar-denominated proof of the flywheel.

The same ground truth for managers, supportively. Check-ins and kudos straight from activity views, an alert when someone's blocked, and chart targets that email you when the projection drifts.

BudgetCapExROI

AI budget burn-down

Spend vs. plan · run-rate projection

This month

Investment classification · Q3

New capability · checkout v2Capitalizable$12,400

New capability · data platformCapitalizable$8,120

Maintenance & fixes$3,080

Investigation & support$1,940

Period locked Oct 1 · full audit trail per classification · illustrative sample data

What the output looks like.

Every week, leaders get a cited narrative report: AI-generated observations about the org, each one linked to the actual sessions behind it.

Observation · org-level

The payments team's migration fix is ready to become a skill

Four sessions this month hit the same migration dead end before a fifth solved it cleanly. Codiedev flagged the working pattern as a skill candidate; promoting it puts the fix in every future migration session automatically.

sess-3011sess-3038skill candidate: phased-migrations

See the full sample insight report →

See the loop on your own work.

In 20 minutes, we'll show you the record of AI work no other platform can produce, and how it compounds.