What stops an agent paying a $20,000 invoice in $499.99 chunks?

Hari Om Garg designs agentic systems for Fortune 500 companies at Wipro, where an agent might approve any invoice under $500 from a known vendor and send anything bigger to a person. Rules like that only hold if the agent can't learn its way around them, and the target is still a 15 to 25% return on investment in the agent's first year in production.

So the sharper question becomes:

How do you give an agent real authority without handing it a loophole?

In this episode of Agents After Dark, Matt Doughty sits down with Hari Om Garg, Managing Consultant at Wipro, to break down how he builds guardrails, confidence thresholds and human review into agentic workflows from the start.

Together they discuss:

• Why the $499.99 trick is a fraud detection problem, and how conditional access rules borrowed from cloud sign-in stop it
• How a confidence wrapper took one agent from 72% to around 90% accuracy, and why anything under 83% goes to a human instead of executing
• Why every engagement starts with a matrix of quick wins and high-impact use cases, each forecast to return 15 to 25% in its first year
• Why agents need their own identities, the way cloud platforms already give services managed identities
• Whether AI ROI is really headcount reduction, and why Hari measures what people do once the agent takes the repetitive work
• Why new use cases should come before rebuilding legacy RPA bots
• What a CEO under pressure should do in the next 30 days: cut the noise, spend two weeks finding real use cases, and ship quick wins inside three months

As agents move from answering questions to approving payments, the rules around them matter as much as the model. Hari treats guardrails as part of the architecture, designed with the use case rather than added after something goes wrong.

This conversation is for CIOs, CTOs and AI leaders who need to show a return on agents this year.

About Hari
Hari Om Garg is an AI solution architect and managing consultant at Wipro, where he designs agentic AI solutions for Fortune 500 companies. He has previously worked at Microsoft, HCL Technologies, LTIMindtree and PowerObjects, and writes for CIO.com on guardrails and intelligent automation for the enterprise.

About Prefactor
Prefactor makes AI agents better.

Prefactor learns how your agents are supposed to behave, evaluates what they actually do on every run, and shows your team how to improve them. Engineers, product managers and the subject matter experts who know what good looks like all work from the same picture, so the agent gets better with every release.

Learn more at prefactor.ai

Only 16% of an engineer's time is spent writing code.

That's the number Adam Witanowski keeps coming back to. Hand your engineers the best coding agent on the market and individuals accelerate 120% to 400%. But you've optimised 16% of the pipeline. Measured end to end, he saw between zero and 40% velocity gain, with everything bottlenecking at the PR.

So the sharper question becomes:

If the coding agents aren't the constraint anymore, what is?

In this episode of Agents After Dark, Matt Doughty sits down with Adam Witanowski, AI architect behind one of Australia's most comprehensive enterprise AI transformations, to break down what it takes to move an organisation up the agentic maturity curve.

Together they discuss:

• Why rolling out a coding copilot and calling the job done just bloats the middle of your delivery pipeline
• The harness he built across the full SDLC, and why rework and incidents beat adoption and token spend as metrics every time
• His audit of 10,000 historical PRs: roughly a third could have been automated, and if you're not ready to automate any of yours, your maturity is lower than you think
• Governor: policy as code injected into coding agents at invocation time and reasserted on CI, so cyber, legal and compliance shape every build without slowing the dev loop. Human in the loop, not human in the way
• Skynet: 3,600 repos ingested into a knowledge graph with decision history, so agents see the downstream impact of a change instead of breaking the team next door
• Why engagement went up while productivity went down, and what job anxiety and a weak front of funnel do to an AI rollout
• Winning over non-engineers: sit with the call centre, find the pain, and sell teams a solution rather than announcing their replacement

His test for where any organisation really sits: maturity isn't about the model. It's about how much you trust the agent when no one's watching it.

This conversation is a practical playbook for any engineering or AI leader trying to turn coding agents from an individual productivity toy into an organisational capability.

About Adam
Adam Witanowski is an AI Executive who spent the past year building one of Australia's most comprehensive enterprise AI transformations from the inside: 11 integrated agentic tools reshaping how engineering teams build software, reimagining the SDLC into an AI-DLC with full executive backing. He shipped 18 products to production in 12 months without writing a meaningful line of code himself.

He is now a consulting Chief AI Officer and keynote speaker on AI-powered engineering, with a background in bioinformatics and, formerly, the best job title in the industry: Chief Officer of Creative AI and Novel Engineering.

About Prefactor
Catch your agents' mistakes before they reach customers.

We evaluate every step your agents take, live. Mistakes get caught as they happen. Not in a Slack thread at 1am on a Tuesday.
Learn more at prefactor.ai

Would Toyota release a car without a seatbelt?

That's the question Sara Abak keeps coming back to. No carmaker would ship a vehicle without safety features, yet the most powerful software ever built ships with no regulation at all. Every single cyber leader she speaks to is worried about frontier AI models.

So the sharper question becomes:

How do you secure the enterprise when AI is moving faster than the rules around it?

In this episode of Agents After Dark, Matt Doughty sits down with Sara Abak, CISO across energy and critical infrastructure, to break down what security leadership actually looks like in the AI era.

Together they discuss:

• Her case for regulating frontier AI like any other product that can cause harm at scale, and why unsafe releases should be paused, not innovation blocked
• How she turns around security cultures in complex organisations: anchor in what the business actually does, because you can't protect what you can't see
• Why CISOs get the "department of no" reputation, and how building trust at board level beats laying down the law
• Why AI features in your ERP or board paper platform stay switched off until they pass a risk assessment
• Shadow AI in practice: locking down what staff can paste into public AI tools, coaching at the point of upload, and quarterly behaviour reporting so decisions are anchored in data and facts
• Why standalone responsible AI programs rarely get funded, and why anchoring AI work inside an existing project with legal, HR, and IT at the table is what actually moves things forward
• How a clinical psychology degree shapes the way she reads the room, wins support, and accepts what she can't change

Her three-part answer to frontier AI risk: regulation, layered foundational controls so you're never the easy target, and holding your vendors accountable. And one rule that applies to all of it: never waste a good incident.

This conversation is a practical guide to enterprise AI security for any leader trying to enable adoption safely while the technology outruns the rulebook.

About Sara
Sara Abak is a Chief Information Security Officer with over 20 years in information security and risk, currently CISO & Industry Leader (Energy & Water) at Grampians Wimmera Mallee Water and Founder of Orca One, a fractional CISO advisory.

Previously CISO and Chief Privacy Officer at Intellihub, she has secured critical infrastructure across Australia and New Zealand spanning IT and OT, led ISO 27001 certification with zero non-conformances, and was recognised as a Most Influential & Top 100 Cyber Security Leader across ANZ in 2025. She is a certified AI governance leader and ISO/IEC 42001 Lead Implementer.

About Prefactor
Catch your agents' mistakes before they reach customers.

We evaluate every step your agents take, live. Mistakes get caught as they happen. Not in a Slack thread at 1am on a Tuesday.

Learn more at prefactor.ai