Deesha AI · SkillLab
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
The 2 days, hour by hour
10 hands-on sessions — every one ends in a thing
Day 1
09:00 – 17:00Ship it
5 sessions09:00 – 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 – 17:00Operate it
5 sessions09:00 – 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.
Request a schedule
Agents in the Wild — Production Agent Lab
Runs on request, for individuals and for teams.
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Who runs it
Practitioners, in the room with you
All trainers and mentorsEach workshop names its trainer before you book.

Vishal Shah
Founder & Principal Trainer
Two decades building and teaching commerce, banking and cloud platforms — still writing code
- Java & Spring Boot microservices
- TypeScript, React, Angular & Next.js
- Composable commerce (commercetools)

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
Running this for a team?
We deliver SkillLabs on site for institutions and engineering teams.
₹2,700
2 days · 16 hours