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1Repair Windows errors before they cause bigger problems2Fix the driver behind crashes, sound loss and screen glitches3Clear out junk files and repair common Windows errors“Wild code” is a sponsored-article term for software, AI agents, and automations created or used across an organization without IT’s knowledge or approval. The risk is not only that a tool may be unsafe: IT may not know it exists, what information it can access, or who is responsible for it. A Tines-sponsored CIO BrandPost argues that conventional code scanning can miss automations built in business workflow platforms and never added to a source-code repository. IBM’s 2026 survey findings offer broader context for why that visibility gap matters, but neither source establishes that every organization has the same problem or that one product solves it.
What “wild code” means—and what it doesn’t
The phrase “wild code” comes from a Tines-sponsored CIO BrandPost published September 30, 2026. It describes ungoverned, unapproved, or simply unseen code and automation spreading inside an organization—not a standardized technical category or a measured industry-wide phenomenon. The article focuses on work created with AI, including applications, agents, and automations that can be built by people outside software-development teams.
This is a visibility problem as much as a code-quality problem. If IT does not know an automation exists, it may be unable to assess the data it touches, its access permissions, its owner, or how it should be maintained. The sponsored article does not establish how prevalent this kind of “wild code” is across organizations.
Why ordinary code controls can miss it
Source repositories and code-scanning tools can reveal issues in software that passes through them. But, as the sponsored CIO article argues, a business-built workflow may live entirely in a workflow platform and never enter a repository. In that case, repository-based scanning cannot find it. Brad Rumph, Field CTO at Tines, put the point this way: “The automation nobody can see is built by people in finance, operations, and HR, who don’t think of themselves as developers. It never enters a repo, so code scanning will never find it.”
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A free scan shows the junk files, broken settings and background clutter dragging Windows down - then fixes them in one click.Free scan · Windows 10 & 11That is a limitation of coverage, not proof that code scanning is useless. Repository scanning still has a role for software that is stored and developed there; it simply cannot provide a complete inventory of activity outside those systems. A visibility effort therefore needs to account for both conventional software-development environments and the business tools where workflows or agents may be created.
What IBM’s 2026 survey adds
IBM’s June 8, 2026 release reports findings from a global survey of 2,000 C-level technology executives. These are responses from the surveyed executives, not a census of all organizations:
- 70% said business teams were deploying technology faster than IT could track.
- 77% said AI adoption was outpacing their organizations’ current governance capabilities.
IBM CIO Matt Lyteson described the challenge as “scaling AI systems that operate continuously and autonomously, often within governance models and architectures designed for a far slower, more predictable environment.” The figures support concern about the pace of deployment and governance, but they do not prove that every organization has an unseen-automation problem or that any particular tool will fix it. IBM’s June 8, 2026 announcement provides the survey context.
What a practical visibility and governance program needs
An inventory is a useful starting point, but it is not a complete governance strategy. The sponsored article’s proposed focus—what exists, what data it touches, and who owns it—can be combined with the broader readiness dimensions IBM identifies: adaptable infrastructure, governance built into systems, and discipline in managing the AI portfolio.
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- Inventory coverage: Identify applications, agents, and automations across source repositories and business workflow tools, rather than assuming one system contains everything.
- Ownership and data touchpoints: For each discovered asset, record an accountable owner and the data it can access or use. An entry without an owner or a clear view of its data exposure is difficult to assess or maintain.
- Governance by design: Put controls into the systems and deployment process where work is created and run, rather than relying only on periodic manual reviews. IBM identifies governance by design as a readiness pillar.
- Infrastructure adaptability: Assess whether the technology foundation can evolve as AI capabilities and deployment needs change.
- Portfolio discipline: Track AI initiatives so leaders can assess investment, adjust efforts, or retire work that is not performing.
IBM’s 2026 Tech Leader Study organizes readiness around those three broader pillars. Its study page also reports that 11% of respondents said they were fully prepared for the scale of AI-agent deployment expected over the next year; that is a survey response, not a direct measure of readiness at every organization.
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Why continuous visibility beats a list of prohibited behaviors
Rules can help define boundaries, but a list of forbidden behaviors can become outdated as tools and practices change. Rumph argued in the sponsored CIO article that “Governance built on predicting specific bad behaviours ages badly,” because “the behaviours change faster than the review cycle that produced the list.” His suggested alternative is continuous visibility into “what AI-generated code and automation exist, what data they touch, and who owns them.”
That recommendation shifts the question from “Which tool should we ban?” to “Can we discover and assess what is actually being used?” It does not remove the need for policy, access controls, or review. Rather, it gives those controls a more current picture of the systems and people to which they need to apply.
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How to assess a proposed solution
The CIO BrandPost describes Tines 3B as a single environment where workflows, agents, and automations are visible from creation. That is a vendor description in sponsored content, not an independent product evaluation. The available evidence does not establish a tested ranking of governance products or verify that any specific product provides complete coverage. When evaluating a platform or internal approach, ask:
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- Which repositories, workflow tools, and other creation environments can it actually see?
- Can it associate each discovered application, agent, or automation with an owner and its data access?
- Are governance controls built into the creation and deployment path, or does the approach depend mainly on periodic manual review?
- Can the organization adapt its infrastructure as AI use changes?
- Can leaders monitor the AI portfolio and decide what to continue, change, or retire?
The sponsored article’s claims about Tines 3B should be weighed as vendor claims; IBM’s survey describes reported organizational conditions, not proof of product effectiveness.
Product prices and availability are accurate as of the date/time indicated and are subject to change. Any price and availability information displayed on Amazon at the time of purchase will apply.
