Automatic

Automatic.co

Agentic AI and automation from the perspective of whoever has to maintain it in six months. Where an agent genuinely belongs in a process, where a plain script is enough, how to design a handoff to a human, and what breaks quietly at scale. Each episode takes one automation decision and reasons it through end to end — including the maintenance burden, the failure modes and the honest question of whether the process should exist at all. Written for operators and technical leads, deliberately free of hype. Five or six minutes an episode. Topics include where an agent belongs versus a plain script, designing human handoffs, error handling and observability, maintenance burden, process mapping before automation, measuring what a workflow saves, and knowing when a process should be deleted instead. Produced by Automatic.co, agentic AI and automation consulting. Full details, services and further reading at https://automatic.co

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49 episodes
a few times a week
Avg 7 min
English

Episodes 49

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August 31 · 8 min
The End of Vendor Lock-In: How On-Prem AI Restores Technical Freedom
Vendor lock-in doesn't start with a bad decision — it starts with a convenient one. This episode breaks down the real cost of cloud AI dependency and why on-premises deployment is the sharpest path back to technical and financial freedom.
August 30 · 8 min
Kubernetes Secrets: Spoiler, They're Not Actually Secret
Kubernetes Secrets sound secure by design — but by default, they're anything but. This episode breaks down why the name is misleading, where credentials actually leak, and what a realistic hardening strategy looks like.
August 29 · 9 min
From Compliance Burden to Compliance Automation With Private LLMs
Compliance teams are drowning in regulatory updates, manual evidence collection, and rigid rule engines — but private large language models are changing that. This episode breaks down how organizations are turning compliance from a costly burden into a se
August 28 · 9 min
Idempotency: Solving the Double-Click Problem for APIs
Duplicate API requests cause real financial and operational damage — idempotency is the engineering discipline that stops them. This episode breaks down how idempotency keys work, where race conditions hide, and how to extend the guarantee across every do
August 27 · 8 min
AI Agents for Finance Teams: Reconciling, Reporting, and Reviewing at Scale
Finance teams still spend most of the close cycle on work that doesn't require expert judgment. This episode breaks down how AI agents handle reconciliation, reporting, and controls at scale — and what it takes to actually trust them.
August 26 · 6 min
How to Scale Your Business with Automation
Growth has a hidden ceiling — and for most businesses, it's a human one. This episode breaks down how to deploy automation strategically across finance, marketing, operations, HR, and AI to scale without burning out your team.
August 25 · 8 min
Building AI Agents You Can Actually Trust in High-Stakes Workflows
AI agents are taking on consequential decisions in finance, law, and healthcare — but can they actually be trusted? This episode breaks down the layered design principles that separate genuinely reliable agents from confidently wrong ones.
August 24 · 8 min
Idempotent APIs: Because Users Always Double-Click
Double-clicks, network retries, and mobile reconnects all send duplicate requests — and most APIs aren't ready for them. This episode breaks down idempotency: what it is, why it matters, and how to build it properly.
August 23 · 9 min
Zero-Trust AI: Building Secure Language Models for Classified Environments
Deploying LLMs in classified environments demands far more than a firewall. This episode breaks down how zero-trust principles—verified identities, scoped permissions, and continuous auditing—can make AI both powerful and genuinely secure.
August 22 · 7 min
Feature Flags at Scale: More Flags, More Problems
Feature flags are a deployment superpower — until they're not. This episode breaks down how flag sprawl quietly becomes an operational hazard at scale, and what engineering teams can do to keep it under control.
August 21 · 7 min
Train Your LLM Like a Partner: AI for Legal Research and Drafting
Most lawyers approach AI like a vending machine — but the real gains come from treating it like a disciplined partner. This episode breaks down a practical, repeatable system for using LLMs in legal research and drafting without the costly surprises.
August 20 · 7 min
Why One-Size-Fits-All AI Is a Lie — And What Actually Works
Generic AI platforms promise everything and deliver friction. This episode breaks down why one-size-fits-all AI fails businesses, what agentic AI actually means beyond the buzzword, and how customized workflows produce results you can measure.
August 19 · 8 min
Stop Renting Intelligence: Why You Should Build Proprietary AI IP
Most companies are renting AI capabilities they'll never truly own — and the hidden costs go far beyond the cloud bill. This episode makes the case for building proprietary AI IP before that dependency becomes a strategic liability.
August 18 · 7 min
Hot vs. Warm vs. Cold Storage: Pick Your Poison
Not all data deserves the same speed — or the same price tag. This episode breaks down hot, warm, and cold storage tiers, what goes wrong when you treat them as interchangeable, and how to build a tiering strategy that actually holds up in production.
August 17 · 8 min
Wiring Your Private LLM Into the Tools Your Team Already Uses
A private LLM locked inside your infrastructure is only half the job — this episode walks through the practical patterns for connecting it to n8n, Zapier, and internal APIs so your whole team can actually use it.
August 16 · 8 min
Graph Databases: When Relational Just Won't Relate
Graph databases flip the relational model on its head — putting connections first instead of columns. This episode breaks down when that shift pays off, how to model and operate graphs in production, and when your trusty SQL setup is still the smarter bet
August 15 · 8 min
Legal AI With No Cloud Required: A New Standard for Confidentiality
Law firms can no longer afford to ignore the question of where client data goes when AI gets involved. This episode explores how on-premise legal AI is reshaping confidentiality standards — and why it's becoming the baseline, not the exception.
August 14 · 7 min
Optimistic Locking: Hope Is a Strategy (Sometimes)
Optimistic locking sounds like wishful thinking, but it's one of the sharpest concurrency tools available — when applied in the right context. This episode breaks down how it works, where it wins, and when to walk away from it.
August 13 · 9 min
Private LLMs for Law Firms: Training AI on Case Law Without Breaking Confidentiality
Law firms are quietly deploying private LLMs to slash research and drafting time — but attorney-client privilege makes the security stakes uniquely high. This episode breaks down the architecture, training techniques, and compliance frameworks making it w
August 12 · 8 min
Data Anonymization: Your Privacy Theater Toolkit
Data anonymization is often more performance than protection — deleting a name and calling it done. This episode breaks down the real techniques, threat models, and governance habits that separate genuine privacy practice from compliance theater.

Showing 21–40 of 49 episodes