Max Tesla for VKTR: why multi-agent workflows break

Blask Co-Founder & CEO Max Tesla just dropped an eye-opening column on VKTR, distilling months of R&D into practical lessons for anyone orchestrating fleets of AI agents. Below is a concise recap, but the full article is well worth the read (link at the end).

Key takeaways

Key takeaways

  1. Why most demo videos collapse in real life
    • Unclear role boundaries lead to duplicated work, infinite loops, or “deadlocks.”
    • Short memory and no shared knowledge base trigger expensive bouts of amnesia.
    • A single failed API call can topple the entire chain if graceful degradation isn’t built in.
  2. Orchestration is the system’s backbone
    A clear decision hierarchy, time-outs, retry policies, and escalation rules turn agent chaos into a manageable project.
  3. Layered memory is non-negotiable
    Short-term (sub-tasks), long-term (strategy), and “team” (collective experience) memories pull agents out of gold-fish mode.
  4. Design for failure, not the happy path
    Fallbacks, task redistribution, and human-in-the-loop triggers are must-haves if you don’t want the first time-out to kill your product.
  5. Optimize for user goals, not “correct” answers
    Ongoing relevance audits and the ability to tweak agents on the fly keep the system aligned with business outcomes.
  6. Benchmarks from the big players
    Amazon Nova: a “Swiss-army knife” for planning, shopping, and booking.
    Microsoft Security Copilot: a mesh of specialist agents for cybersecurity.
    Waymo Carcraft: a sim-city where driver agents learn not to crash.
    AWS Bedrock: a Lego-style platform for assembling collaborative agents.

Why it matters for Blask

Blask ingests thousands of iGaming signals every hour. Our own pipelines already behave like an agent orchestra: CV models watch casino lobbies, NLP models parse brand content, and rankers crunch BAP, APS, and CEB.

Max’s column lifts the curtain on the engineering “kitchen” behind that resilience — from redundant tracking agents to a multi-level memory store that prevents metrics from “forgetting” yesterday’s context.

For operators and providers, this means one thing: Blask data doesn’t crumble under traffic spikes or API hiccups, so your decisions stay sharp even in volatile times.