🎮 The Next Input — Issue #183

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⚡ The Briefing — 60 sec

• NVIDIA launches another AI infrastructure push And just like that NVIDIA said: "Here's another reason to keep paying us." At this point they're less a chip company and more a toll road for the AI economy.

• GitHub Copilot's new token-based billing sparks developer backlash Hurts to see as an ex-Hubber, but no two ways around it. They bunged this one. Developers generally tolerate a lot. Feeling like you're getting nickel-and-dimed is not one of them.

• Anthropic releases Claude Opus 4.8 Gotta be honest. As someone using these models every day? GPT-5.5 still takes the crown for me right now. Your mileage may vary, but that's where my chips are sitting.

🛠️ The Playbook — AI Vendor Escape Hatch

Mission
Build AI infrastructure that lets you switch models, pricing plans, and providers without rebuilding your business every six months.

Difficulty
Intermediate

Build time
3–5 hours

ROI
Protects against vendor lock-in, pricing shocks, model regressions, and platform strategy changes.

0) Why This Matters

One of the biggest mistakes companies are making right now?

Building their entire AI strategy around a single vendor.

Models change.

Pricing changes.

Features disappear.

Roadmaps shift.

The businesses that survive the next five years won't necessarily pick the "best" model.

They'll build systems that can swap models without causing operational heart attacks.

1) Architecture

2) Workflow

1. User submits a request through an approved interface.

2. Routing logic evaluates complexity, latency requirements, and cost targets.

3. Request is assigned to the most appropriate model.

4. Retrieval grounding injects company-specific context.

5. Results are evaluated against quality thresholds.

6. Performance and cost metrics are logged continuously.

3) Example Prompts

Model Selection Prompt

You are an AI orchestration layer.

Determine which model should handle this task.

Consider:
- complexity
- latency requirements
- cost sensitivity
- reasoning depth
- retrieval needs

Return:
1. recommended model
2. confidence score
3. justification
4. fallback model

Vendor Risk Prompt

Analyse the following AI architecture.

Identify:
- vendor lock-in risks
- pricing exposure
- migration complexity
- operational dependencies
- resilience weaknesses

Recommend mitigation strategies.

Model Benchmark Prompt

Compare outputs from multiple AI models.

Evaluate:
- accuracy
- reasoning quality
- speed
- cost efficiency
- consistency

Provide a ranking and recommendation.

4) Guardrails

• Never hard-code workflows to a single model provider.

• Maintain at least one tested fallback model.

• Separate business logic from model logic.

• Benchmark models quarterly.

• Track cost per workflow continuously.

• Maintain exportable prompt and workflow configurations.

5) Pilot Rollout — 3 hours

1. Identify one AI workflow currently dependent on a single vendor.

2. Add a second model provider.

3. Implement routing logic between providers.

4. Run side-by-side quality testing.

5. Track performance and cost differences.

6. Document migration procedures and failover processes.

6) Metrics

• Cost per workflow

• Model response latency

• Output quality score

• Vendor dependency ratio

• Failover success rate

• User satisfaction

• Monthly AI spend

Pro Tip: The most expensive AI migration is the one you discover you can't perform.

🎯 The Arsenal — Tools & Platforms

• OpenAI GPT-5.5 · primary reasoning and workflow execution · Link

• Anthropic Claude · secondary reasoning and failover capability · Link

• Pinecone Pinecone · retrieval and institutional memory · Link

• Grafana Labs Grafana · cost and performance monitoring · Link

• PostgreSQL PostgreSQL · auditability and operational logging · Link

Copy-paste prompt block:

You are an AI infrastructure architect.

Design a vendor-agnostic AI platform.

Requirements:
- support multiple AI providers
- minimise vendor lock-in
- optimise cost and quality
- provide failover capability
- maintain auditability
- support future model changes

Return:
1. architecture
2. routing logic
3. governance controls
4. failover strategy
5. operational metrics
6. migration procedures

💡 Free Office Hours

A surprising number of businesses are treating AI vendors like permanent infrastructure. History suggests most technology winners eventually get disrupted, repriced, or replaced.

Book here: https://calendly.com

Tabs + PwC: Pricing Playbook for the AI Era

Pricing models are evolving fast—and finance teams are feeling it. Usage-based and hybrid structures unlock new revenue potential, but they also create real challenges around rev rec, forecasting, and scaling operations.

On June 10th, leaders from Tabs and PwC are going live to share how modern B2B companies are navigating this shift—with practical frameworks and real-world examples you can actually use.

Save your spot for the live session on June 10th, 1–2PM EDT. Can't join live? Register anyway—the recording will be sent straight to your inbox.

Register Now

🕹️ Game Over

The model wars are fun to watch.

The businesses quietly building escape hatches are probably making the smarter bet.

— Aaron Automating the boring. Amplifying the brilliant.

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