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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41 episodes
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Avg 8 min
English

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Today · 4 min
Memory Leaks in Serverless: Still a Thing
Serverless promised fewer headaches — but memory leaks didn't get the memo. This episode unpacks why leaks are sneakier than ever in serverless environments and what engineering teams can actually do to catch them.
Tuesday · 4 min
Machine Learning Models: Overhyped or Just Underfed?
Most machine learning projects don't fail because the algorithm is wrong — they fail because the model is starved of good data. This episode breaks down the real culprits behind ML underperformance and what teams should fix first.
September 10 · 5 min
Message Brokers: Who's Actually in Charge Here?
Message brokers promise smooth data flow in distributed systems — but who's really holding the reins? This episode unpacks the control-vs-coordination split that determines whether your architecture scales cleanly or quietly turns into infrastructure spag
September 8 · 5 min
Why Your Failover Isn't Actually Failing Over
Your load balancer is configured, your standby is ready, and your runbook is polished — so why does traffic still pile up when a node goes dark? This episode breaks down the hidden configuration gaps that make failover fail silently.
September 8 · 10 min
Can Private LLMs Actually Fix the Hallucination Problem in Enterprise AI?
Private LLMs promise to tame enterprise AI hallucinations — but the fix isn't the model itself. This episode breaks down why hallucinations happen, where private deployment genuinely helps, and what governance actually needs to look like.
September 7 · 9 min
Interoperability Nightmares: How to Wake Up from Your Data Silos
Data silos aren't just annoying — they're quietly rotting your organization's decision-making from the inside. This episode breaks down how interoperability failures happen, why your tech stack makes them worse, and what a real escape plan looks like.
September 6 · 9 min
Why General-Purpose AI Falls Short in Regulated Workflows
General-purpose AI can sound confident and move fast — but in regulated industries, fluent answers aren't the same as defensible ones. This episode breaks down exactly where off-the-shelf AI falls short when compliance, audit trails, and role-based author
September 5 · 9 min
Incremental Backfills: How to Rewrite Data History Without Breaking Everything
When upstream data definitions change, reloading entire tables from scratch is slow, expensive, and unsustainable. This episode breaks down how incremental backfills let data teams correct historical data precisely — without blowing up production or the c
September 4 · 8 min
Why Healthcare and Government Are Going All-In on Private AI
Healthcare systems and government agencies are ditching public AI endpoints in favor of private deployments that keep sensitive data locked inside their own walls — and the results are rewriting what regulated industries thought was possible.
September 3 · 8 min
Kernel Tuning: Because Defaults Are for Amateurs
Your OS defaults were designed for nobody in particular — and your production workload isn't nobody. This episode breaks down kernel tuning: what to measure, which levers move the needle, and how to make performance gains that actually stick.
September 2 · 8 min
The Anatomy of a Secure AI Knowledge Base
Building an AI knowledge base without security built into its foundation isn't just risky — it's an organizational liability. This episode breaks down every architectural layer that separates a trustworthy private AI system from a breach waiting to happen
September 1 · 7 min
LLM Guardrails: Not Just for PR Anymore
LLM guardrails have graduated from slide-deck buzzword to operational necessity. This episode breaks down the three-layer framework that separates companies building trustworthy AI from those one rogue output away from a compliance crisis.
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.

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