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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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  • 43 episodes
  • Avg 8 min
  • English
Counted on this page — what you have heard stays on this device, so it is not something the list can be paged by.
  • 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 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 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 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 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 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.

  • August 11 · 8 min

    Private vs. Public LLMs: What Every CTO Needs to Know

    Choosing between a public or private LLM isn't just a technical call — it's a strategic one with major implications for security, cost, and competitive advantage. This episode breaks down exactly what CTOs need to weigh before committing.

  • August 10 · 9 min

    Real-Time Joins: Making SQL Cry

    Joining live data streams sounds straightforward — until latency, late events, and memory bloat turn your pipeline into a nightmare. This episode breaks down why real-time joins are so hard and how to engineer them without losing your mind.

  • August 9 · 10 min

    LLMs Behind Closed Doors: Building Secure, In-House AI Models

    Enterprise AI teams are moving LLMs behind the corporate firewall — and for good reason. This episode breaks down the security architecture, hardware choices, and operational discipline required to run private, self-hosted language models at scale.

  • August 8 · 9 min

    ACID vs. BASE: The Database Cold War

    ACID and BASE aren't just database acronyms — they're competing philosophies about trust, scale, and the promises software makes to users. This episode breaks down both models, their real-world tradeoffs, and how to choose — or combine — them wisely.

  • August 7 · 9 min

    The Rise of On-Prem LLMs: Control, Compliance, and Customization

    Cloud AI is convenient — until legal asks where your data actually goes. This episode breaks down why on-premises large language models are becoming a serious enterprise strategy, covering data sovereignty, compliance, cost curves, and how to build it rig

Showing 21–40 of 43 episodes