Before commissioning custom AI software, name the requirement your existing tools cannot meet. It might be a workflow that must run continuously, a connection between systems, or a control the business needs. That requirement should explain what the extra build will accomplish.
If the answer is still unclear, Sidekick recommends testing the work inside tools your team can already use. Start with enough structure to make one useful change. Add custom software when a real limit appears.
Define the work before the system
A proposal can include several AI agents, a database, a dashboard and connections to business software. Those components may be necessary. A diagram alone cannot tell you whether they are.
First, describe the work in ordinary terms. Perhaps staff need to prepare proposals with less repeated research. Perhaps meeting commitments keep disappearing, or a weekly report depends on one person finding information across several systems. These are illustrative situations, not Sidekick client results.
For the work you choose, identify the information it needs, who will use the result and which decisions remain human. Agree on what improvement would justify keeping it. That gives you something concrete to test before deciding how much software to build.
An existing AI workspace may be enough
An AI workspace can hold useful source material and instructions for repeated work. OpenAI documents files, project instructions and connected apps in ChatGPT Projects. Anthropic documents project knowledge and instructions in Claude Projects.
Available features depend on the product, plan and workspace permissions. A saved instruction or connected tool does not, by itself, establish that a workflow is reliable or allowed to act on the business’s behalf.
The design work still matters. The AI needs the right sources, a clear task and a defined point to return work for review. Someone must know how to check the result and recover when it fails. Relationships, commitments and important decisions need an accountable person.
This can be a useful first version even when it has no separate website or custom dashboard.
When custom software makes sense
Custom work becomes easier to justify when you can point to a requirement such as:
- The volume makes manual operation or review impractical.
- The workflow must run continuously or respond within a fixed time.
- Several systems need dependable, structured exchanges of information.
- Access, audit or data-location requirements need controls the current platform cannot provide.
- The people doing the work need the function inside software they already use.
These are reasons to examine a custom build. They do not establish that any proposed build will meet the requirement. The implementation still needs to be checked against the actual work.
A general AI workspace may be the wrong starting point when an essential requirement is already known. There is no benefit in forcing a trial through a tool that cannot meet it.
Include the cost of keeping it working
The initial build is only part of the decision. Someone must maintain connections, control access, investigate failures and manage usage costs. Ask who will do that work after the original builder leaves.
Existing platforms also need ownership. The provider maintains the product; the business still needs to manage its information, permissions and use. Compare both options on the full operating burden, including the work your team will carry.
The useful comparison is specific: which option can support this workflow, at an acceptable cost, with responsibilities the business can sustain?
Questions to bring to a proposed build
Before approving the work, ask:
- What business outcome should change?
- What is the simplest workflow that could test that change?
- Which requirement cannot be met inside the tools we already have?
- Who will operate and maintain the custom parts, and what will that cost?
- What evidence would tell us to expand, change or stop?
Use the answers to narrow the proposed build. If a workflow reaches a real limit, you should be able to explain what the next component must do.
See how Sidekick takes work from a first decision to everyday use.
