You probably pay for four or five specialized AI tools right now. One reviews code. Another orchestrates agents — autonomous AI programs that do tasks for you. A third manages your team's knowledge base. Each one a startup built on doing that one thing well.

Your CFO just noticed the combined bill. Here is the framework for deciding what stays, what goes, and what you never should have bought.

Why this matters right now

Over the past two weeks, the platforms you already pay for started absorbing the features startups sold you as standalone products.

On March 30, Qodo raised $70M for AI code review — betting the standalone market still has room. Room for what, exactly? By early April, GitHub had expanded Copilot code review to 12,000+ organizations, adding active-versus-passive review tracking on April 6 and a merge metrics API on April 8. The platform keeps closing the gap.

On March 31, Salesforce turned Slack into an agentic operating system: 30+ AI features, an MCP client — a universal connector that lets AI plug into other tools, like USB but for software — and access to 6,000 existing integrations. Marc Benioff: "Some saw a messaging app. We saw the foundation for the Agentic Enterprise."

On April 8, Anthropic launched Managed Agents — cloud-hosted agents with sandboxed execution, state management, and multi-agent coordination. Price: your Claude model usage plus $0.08 per agent runtime hour.

We have covered each of these shifts individually. This article gives you the rubric to act on all of them at once.

Your consolidation question is no longer theoretical. Here is how to answer it.

The four-question rubric

For every AI tool on your team's invoice, ask these four questions in order. If a tool fails any of the first three, it is a cut candidate.

1. Does your existing platform already do this?

Check the feature changelogs of GitHub, Slack, Notion, your cloud provider, and your IDE. If the platform added the capability in the last 90 days, the standalone tool lives on borrowed time.

GitHub Copilot now reviews pull requests automatically for 12,000+ organizations. Slack runs agents natively. Anthropic hosts and orchestrates agents for $0.08 per runtime hour plus model usage. The "we do it better" argument has a shelf life measured in product cycles, not years.

If yes → strong cut candidate. Move to question 4 only to check switching cost.

2. Does the tool touch domain-specific data the platform cannot access?

Healthcare compliance. Legal precedent databases. Financial regulatory workflows. If the tool's value depends on proprietary domain data, vertical expertise, or regulatory certification, no platform toggle replaces it.

On April 9, PYMNTS reported that the startups most at risk from Anthropic's Managed Agents are horizontal ones — code review, workflow automation, agent orchestration, AI search — holding no unique data advantage. Sierra, noted in the same April 9 report at a $10B valuation and $100M in annual revenue, survives precisely because of its moat: proprietary customer service data and domain expertise no platform can replicate with a settings toggle.

If yes → keep. The platform cannot replicate this with a settings toggle.

3. Does the tool own a feedback loop the platform lacks?

Some tools improve because they see data the platform never will. A security scanner that trains on your organization's specific vulnerability patterns. A testing tool that learns from your failure modes. If the tool gets smarter from data that stays inside it and never reaches the platform, that is a defensible position.

If yes → keep, but reassess quarterly. Platforms aggressively expand their data access.

4. What does switching actually cost?

Even when a platform replicates a feature, switching has friction: workflow migration, team retraining, integration rewiring, and the productivity dip during transition. Calculate the real cost, not the theoretical savings.

A tool that fails questions 1–3 but supports 200 engineers with custom workflows might still deserve a six-month migration runway — not a Friday afternoon cancellation.

High switching cost → schedule a migration, don't skip it. Low cost → cut this week.

Apply the rubric: three examples

AI code review (Qodo, CodeRabbit, etc.)

  • Q1: GitHub Copilot does this natively. ✓ Cut candidate.
  • Q2: No domain-specific data moat. Generic code review.
  • Q3: No unique feedback loop GitHub cannot replicate.
  • Q4: Low switching cost — disable one, enable the other.
  • Verdict: Cut.

Agent orchestration (LangChain, CrewAI, etc.)

  • Q1: Anthropic Managed Agents does this natively. ✓ Cut candidate.
  • Q2: No domain data moat.
  • Q3: Framework lock-in creates friction, not defensibility.
  • Q4: Medium switching cost — refactoring agent code takes time.
  • Verdict: Cut, but budget a migration sprint.

Vertical healthcare AI (compliance, clinical documentation)

  • Q1: No platform offers this as a toggle.
  • Q2: Proprietary clinical data, regulatory expertise. ✓ Keep.
  • Q3: Trains on institution-specific patterns. ✓ Keep.
  • Q4: Not applicable.
  • Verdict: Keep. This is a moat.

The uncomfortable math

On April 10, Crunchbase reported Q1 2026 venture funding hit a record $300 billion — but 65% went to just four companies: OpenAI, Anthropic, xAI, and Waymo. The money flows to platforms, not point solutions.

The stock market agrees. On April 9, CNBC reported that Anthropic's Managed Agents launch triggered a SaaS selloff: Akamai dropped 16.6%, Cloudflare 13.5%, DigitalOcean 13.4%. Analyst Ben Reitzes of Melius Research: "We've lost $1.4 trillion in SaaS market cap since Anthropic was worth just $18 billion in January 2025."

This is not a signal to panic. It is a signal to consolidate deliberately — before your CFO does it for you with a spreadsheet and no context.

The rubric in one line

If a platform you already pay for can do it, and the tool holds no domain data or unique feedback loop, cut it. Everything else, keep — but put a review date on the calendar. ⚙️