While agile development is hard in hardware
Hardware engineering is not possible without cross-functional teams: mechanical, electronics, firmware, reliability, quality, and more. Each of these teams have different priorities, different development cycles, and use different tools. This creates a burden on engineering and product managers who need to interact with multiple teams to deliver the products to the market. This coordination requires a lot of bandwidth to manage, and as teams grow, gaps begin to show up in execution.
How do you resolve these gaps currently? If you’re a member of an engineering team who notices a gap in delivery between teams, you flag this immediately to your manager. Your manager brings it up to the managerial level, so that it can be prioritized by the manager of the team best positioned to address it. Your colleague on the next team will learn about it from their manager. This vertical process of coordination ensures adequate prioritization but is inefficient for a fast-moving hardware cycle.
What your team needs is to get immediate context on how long it will take to resolve that gap the moment you notice it. You need the engineer on the other team to give you an update yesterday, you need cross-coordination. In reality, that engineer is as busy as you are, also working on tasks to bring the product to market as fast as possible.
You need access to the information already in your systems to begin resolving these gaps. As hardware teams get more successful, with more product lines, SKUs, versions, cross-coordination with people does not scale. If you’re adding even one more product line, you don’t add 1 more channel, but N more channels where N is the number of cross-functional teams you have.
What scales better? AI orchestration in two steps.
First, you need a layer that sits on top of the tools that your engineering team is already using but without disrupting the workflows of your team members.
Then, you need context on previous related issues, interdependencies between teams and programs, and an understanding of the priorities of the other teams.
These are tasks that AI is perfect for and can do proactively, so you have the information when you need it. Traditional tools won’t help you stay lean and agile.
That’s why EverCurrent exists, to get information from where it’s generated to where it’s needed, so that your engineering team stays lean and fast. We are the team AI that captures progress as the work happens, maintains context across product lines and product variants, to help teams close gaps faster without meetings.