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WorkshopRuns on requestAI & Agentic AIAgentsDeploymentState persistenceObservabilityDocker

Agents in the Wild: Production Agent Lab

Two hands-on days taking an agent from a working demo to a production system: containerised and deployed, its state persisted across restarts, failures handled without losing work, every run observable, and the operating rules written down before real users arrive.

Designed for

  • Developers whose agent works on their laptop and nowhere else
  • Teams about to put an agent in front of real users or real workflows
  • Engineers who have never restarted an agent mid-task and watched what happens
  • Anyone responsible for an agent's behaviour at 2 a.m.
Fee
₹2,700
Duration
2 days · 16 hours
Each day
09:00 – 17:00
Mode
Offline / Online
Request a schedule

The 2 days, hour by hour

10 hands-on sessions: every one ends in a thing

Day 1

09:00 – 17:00

Ship it

5 sessions

09:00 – 10:15

See why laptop agents die in production

the demo-to-production gap, state and secrets audit, the plan

Takeaway Your agent's hidden assumptions listed: every path, key and in-memory state that will not survive a deployment.

10:30 – 11:45

Containerise the agent

images for agent workloads, configuration, secrets at runtime

Takeaway The agent in a container, configured from outside, with a planted secret kept out of the image and proved absent.

12:00 – 13:00

Deploy it as a service

the agent behind an API, health checks, versioned prompts and tools

Takeaway Your agent reachable as a deployed service with a health check that means something, and a version you can name.

14:00 – 15:15

Persist the state that matters

task state in a real store, resumability, what not to persist

Takeaway A long task killed halfway and resumed exactly where it stopped, because its state lives in a database, not a variable.

15:30 – 17:00

Handle the failures that will happen

tool outages, model errors, timeouts and compensation

Takeaway A tool taken down mid-task on purpose: the agent degrading, retrying and completing without corrupting anything.

Day 2

09:00 – 17:00

Operate it

5 sessions

09:00 – 10:15

Trace every run

run traces, step attribution, token and cost per task

Takeaway Twenty production-shaped runs on one dashboard: the expensive one found and explained in under a minute.

10:30 – 11:45

Budget and bound the fleet

concurrency and queues, rate limits, cost ceilings per task

Takeaway Fifty tasks submitted at once and handled on your terms: queued, bounded and each under its own cost ceiling.

12:00 – 13:00

Keep humans in the loop at scale

approval queues, escalation paths, audit trails

Takeaway Approvals arriving in one queue a human can actually work, with every decision recorded for the audit that will come.

14:00 – 15:15

Rehearse the bad day

incident drill, the kill switch, stopping without losing work

Takeaway A live incident drill: the agent misbehaving on cue, caught by its traces, and stopped with the kill switch you tested.

15:30 – 17:00

Write the runbook and hand it over

what to monitor, when to intervene, handover review

Takeaway A one-page runbook another engineer could operate your agent from, reviewed by the room as the final exercise.

By the end of day 2, you are holding

Your own agent running as a deployed service: containerised, its task state in a real store, resuming cleanly after a mid-task kill, its runs traced and budgeted, with an operating runbook and the escalation rules a team could actually follow.

No dates announced

We open batches around demand. Tell us the schedule that would work and we will let you know first.

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How will you join?

Laptop ready with the prerequisites?

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Who runs it

Practitioners, in the room with you

All trainers and mentors

Each workshop names its trainer before you book.

  • Vishal Shah

    Vishal Shah

    Founder & Principal Trainer

    Two decades building and teaching commerce, banking and cloud platforms, and still writing code

    • Java & Spring Boot microservices
    • TypeScript, React, Angular & Next.js
    • Composable commerce (commercetools)
    Full profile →
  • Shrenik Shah

    Shrenik Shah

    Principal Trainer

    Cloud and AI architect who has upskilled over 5,000 engineers in Java, React, Python and cloud

    • Python: Django, Flask, GenAI & agentic workflows
    • Java & Spring Boot
    • React & Angular, micro-frontend architecture
    Full profile →

Running this for a team?

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₹2,700

2 days · 16 hours

Request a schedule