> ## Documentation Index
> Fetch the complete documentation index at: https://docs.decimal.ai/llms.txt
> Use this file to discover all available pages before exploring further.

# DecimalAI for Engineers

> Shipping agents to production safely. The deploy-safety reading path: traces, manifests, regression checks, and CI integration.

If you ship agent code to users — and your job is to make sure agent changes don't silently break in production — this is your reading path. The goal: by the end you have **automatic, pre-deploy structural impact analysis on every PR**, and **post-deploy regression bisect** if something does break.

<Note>
  This page is a curated reading path, not new material. Every link goes to an existing guide. Treat it as the "what to read in what order" map.
</Note>

## The problem this page solves

Agents are non-deterministic by nature, but their *configuration* — prompts, tools, models, output schemas, sub-agent topology — is deterministic. DecimalAI fingerprints that configuration into a **manifest**, attaches the manifest to every trace, and uses manifest-diffs to predict what changes in your code will break what production traffic.

You don't write eval cases up front. You don't pause to define "correctness." You ship code and get a structural impact report on the PR.

## Reading path (in order)

<Steps>
  <Step title="Step 0 — see the payoff on seeded data (2 minutes)">
    Before touching your agent, run the sandbox so you know what you're wiring up:

    ```bash theme={null}
    pip install decimalai          # Python 3.10+
    decimalai demo regression      # → a live impact report on a seeded v1→v2 change
    ```

    [2-Minute Demo walkthrough](/tutorials/two-minute-demo) explains what the report is telling you.
  </Step>

  <Step title="Get your first trace in under 5 minutes">
    [Quickstart](/quickstart) — install, init, see a trace land in the dashboard.

    Pick the tab for your framework. If you're using something we don't have a tab for, see [generic OTel](/sdk/python/frameworks/otel).
  </Step>

  <Step title="Understand what's actually being captured">
    [Tracing guide](/guides/tracing) — what counts as a trace, what counts as a span, what gets serialized and what doesn't.

    [Manifests guide](/guides/manifests) — the deterministic fingerprint of your agent. Read this carefully; it's the foundation everything else builds on.
  </Step>

  <Step title="Wire the GitHub Action">
    [Regression Check guide](/guides/regression-check) — the GitHub Action that posts a manifest-impact comment on every PR.

    This is the workflow that gives you the killer outcome: a PR that changes the agent's tools gets `🔴 HIGH IMPACT — 247 traces will break (called the removed tool)`.
  </Step>

  <Step title="Understand the severity bands">
    [Compatibility Policies guide](/guides/compatibility-policies) — how `high_risk` / `medium_risk` / `low_risk` are computed and how to tune the thresholds.

    Read this before you start ignoring the action's verdicts. The defaults are conservative on purpose.
  </Step>

  <Step title="Set up post-deploy bisect">
    [Post-deploy bisect guide](/guides/post-deploy-bisect) — what to do when a regression slips through and you need to find *which* manifest version introduced the bad behavior.

    This is the workflow you'll reach for at 3am when your agent suddenly stops calling a critical tool.
  </Step>

  <Step title="Wire replay for the medium-risk cases">
    [Replay guide](/guides/replay) — for the changes the regression check can only label `medium_risk`, replay surfaces the actual behavioral diff by re-running historical inputs through both manifests.
  </Step>
</Steps>

## What you can skip (for now)

| Feature         | Skip if...                                                                                                                                                                | Read it when...                                                                                                         |
| --------------- | ------------------------------------------------------------------------------------------------------------------------------------------------------------------------- | ----------------------------------------------------------------------------------------------------------------------- |
| **Evaluations** | You only want deploy-safety value. The 5 built-in checks run automatically on every trace and give you `keep / repair / replay / drop` verdicts — no eval cases required. | You have a specific quality regression you want to write a check for. See [the evaluations guide](/guides/evaluations). |
| **Datasets**    | You're not training models. Datasets are the export pipeline (trace → JSONL → fine-tuning).                                                                               | You want to turn traces into training data. See [the datasets guide](/guides/datasets).                                 |
| **Skills**      | You have a single agent. Skills are reusable agent knowledge files — an optional add-on.                                                                                  | You have multiple agents that share knowledge. See [the skills guide](/guides/skills).                                  |

## The five files you'll actually touch

| File                                   | What you change it for                                                      |
| -------------------------------------- | --------------------------------------------------------------------------- |
| `scripts/init_for_decimal.py`          | Once. Calls your agent factory so the regression check knows your manifest. |
| `.github/workflows/decimal.yml`        | Once. Wires the GitHub Action.                                              |
| Your agent code                        | Add `decimalai.init(api_key=..., <framework>=True)` once. Never again.      |
| `compatibility-policy.yaml` (optional) | When you want to tune what counts as `high_risk`.                           |
| `pyproject.toml` / `requirements.txt`  | When you upgrade the SDK.                                                   |

That's the entire integration surface for the deploy-safety workflow.

## Failure modes and where to look

| Symptom                                     | Where to start                                                                                                           |
| ------------------------------------------- | ------------------------------------------------------------------------------------------------------------------------ |
| Action doesn't comment on PR                | [Regression Check guide → Troubleshooting](/guides/regression-check)                                                     |
| Action says "no baseline"                   | You haven't ingested a manifest in production yet. Deploy once, then run the action.                                     |
| Action says `high_risk` on a no-op refactor | Manifest is hashing something it shouldn't (e.g. dynamic prompt). See [Manifests guide → False drift](/guides/manifests) |
| Production trace volume dropped to zero     | Check [Webhooks](/guides/webhooks) for alert config; check the dashboard's volume chart                                  |

## When to talk to the platform-team page instead

If your job is more about *operating* DecimalAI itself — wiring webhooks to PagerDuty, configuring teams + RBAC, debugging multi-agent flows — read [DecimalAI for Platform Teams](/for-platform-teams).

## What's next

<CardGroup cols={2}>
  <Card title="Quickstart" icon="play" href="/quickstart">
    Start at the top.
  </Card>

  <Card title="Regression Check" icon="shield-check" href="/guides/regression-check">
    The killer workflow for engineers.
  </Card>
</CardGroup>